{ "schema": "vxm-casebook-release/1", "title": { "en": "Vinum ex Machina — Casebook", "ru": "Vinum ex Machina — «Кейсбук»" }, "description": { "en": "A catalogue of 299 documented deployments of artificial intelligence in viticulture, winemaking and the wine business. Behind each record is a source that was opened and read, and a statement of what that source does and does not support. Every record was reopened against its sources in a full audit.", "ru": "Каталог из 299 задокументированных внедрений искусственного интеллекта в виноградарстве, виноделии и винном бизнесе. За каждой записью стоит источник, который был открыт и прочитан, вместе с указанием на то, что он подтверждает, а чего не подтверждает. Все записи заново открывались по источникам в ходе сплошного аудита." }, "url": "https://vinumexmachina.com/casebook/cases/", "about": "https://vinumexmachina.com/casebook/", "version": "v2026-09-29", "generated": "2026-09-29", "corpusVersion": "v2", "license": "CC BY-SA 4.0", "licenseUrl": "https://creativecommons.org/licenses/by-sa/4.0/", "attribution": "Vinum ex Machina — Casebook v2026-09-29, Nikita Khudov, CC BY-SA 4.0, https://vinumexmachina.com/casebook/cases/", "creator": { "name": "Nikita Khudov", "url": "https://vinumexmachina.com/about-author/" }, "recordCount": 299, "sourceCount": 314, "fieldCount": 35, "languages": [ "ru", "en" ], "distribution": [ { "file": "casebook-v2026-09-29.json", "url": "https://vinumexmachina.com/casebook/casebook-v2026-09-29.json", "format": "JSON", "mediaType": "application/json", "bytes": null }, { "file": "casebook-v2026-09-29.csv", "url": "https://vinumexmachina.com/casebook/casebook-v2026-09-29.csv", "format": "CSV", "mediaType": "text/csv; charset=utf-8", "bytes": 339756 } ], "notes": { "identifiers": { "en": "Two numbers identify a record and they are not the same number. `id` is a compacted 1–299 renumbering with no gaps; `catalogId` is the source catalogue's original sequence, 1–307 with eight gaps, and it differs from `id` on 276 of the 299 records. Join on `id`. Joining two exports of this corpus on `catalogId` — or joining one of each — produces a convincing false positive of a handful of records \"only in each\" rather than an error.", "ru": "Запись опознаётся двумя числами, и это разные числа. `id` — сплошная перенумерация 1–299 без пропусков; `catalogId` — исходная нумерация каталога, 1–307 с восемью пропусками, и она отличается от `id` у 276 записей из 299. Соединять следует по `id`. Соединение двух выгрузок этого корпуса по `catalogId` — или одной по одному ключу, а другой по другому — даёт не ошибку, а убедительное ложное совпадение: несколько записей окажутся «только в одной из выгрузок»." }, "sources": { "en": "Every one of the 299 records carries at least one source with a resolvable http(s) URL — 314 sources in all. That is a condition of entry rather than a property of the sample: a mention without a link, a link without a page and a page without grapes did not become a record. The `confidence` facet grades that source, and it grades the source rather than the case.", "ru": "У каждой из 299 записей есть хотя бы один источник с рабочим http(s)-адресом — всего источников 314. Это условие попадания в корпус, а не свойство выборки: упоминание без ссылки, ссылка без страницы и страница без винограда записью не становились. Фасет `confidence` оценивает именно источник, а не кейс." }, "aiKind": { "en": "`aiKind` is not one of the facets and is not meant to be filtered on: the overwhelming majority of records sit in one value, so a filter built on it selects everything by default. It is published as a label on the minority, and `flags.nonAi` lists exactly which records those are.", "ru": "`aiKind` не входит в число фасетов и не предназначен для фильтрации: подавляющее большинство записей стоит в одном значении, так что фильтр по нему по умолчанию выбирает всё. Он опубликован как пометка на меньшинстве, и `flags.nonAi` перечисляет, на каких именно записях." }, "languages": { "en": "Every record is published in both languages, field by field: a `…Ru` field is empty if and only if its `…En` counterpart is. The corpus was researched in Russian and translated, so the Russian is the original and the English is the translation of it — not the other way round, and never a fallback.", "ru": "Каждая запись опубликована на двух языках, поле в поле: поле `…Ru` пусто тогда и только тогда, когда пусто парное `…En`. Корпус собирался по-русски и затем переводился, поэтому русский текст — оригинал, а английский — его перевод, а не наоборот и не подстановка." }, "absences": { "en": "A field the source does not fill is published as an empty string rather than being left out, so every record carries every column and the CSV and the JSON describe the same shape. An empty value is a statement about the cited source, not a gap in the catalogue.", "ru": "Поле, которого источник не заполняет, публикуется пустой строкой, а не пропускается: у каждой записи есть каждая колонка, и CSV с JSON описывают одну и ту же форму. Пустое значение — утверждение о цитируемом источнике, а не дыра в каталоге." }, "notPublished": { "en": "The audit's own columns — the verdict on each record, the action it required, what the check found — are not published here or anywhere. They record how the corpus was checked, not the corpus. What is published is the consequence: corrected text, and a caveat beside the figure the source does not support.", "ru": "Внутренние колонки аудита — вердикт по записи, требуемое действие, «что показала проверка» — не публикуются ни здесь, ни где-либо ещё. Это запись о том, как проверяли корпус, а не сам корпус. Публикуется следствие: исправленный текст и оговорка рядом с цифрой, которую источник не подтверждает." }, "completeness": { "en": "The catalogue is knowingly incomplete: it holds what is published and checkable, not everything that happens. It measures nothing, ranks no one and forecasts nothing — the `stage` facet says where a case stands and is not a score.", "ru": "Каталог заведомо неполон: в нём то, что опубликовано и проверяемо, а не всё, что происходит. Он ничего не измеряет, никого не ранжирует и ничего не прогнозирует — фасет `stage` говорит, где кейс находится, и оценкой не является." }, "links": { "en": "Each record's `url` is the English register anchored at that record. The Russian mirror is the same anchor one path segment over: https://vinumexmachina.com/ru/casebook/cases/#case-.", "ru": "Поле `url` каждой записи — это английский реестр с якорем на ней. Русское зеркало отличается одним сегментом пути: https://vinumexmachina.com/ru/casebook/cases/#case-." }, "csv": { "en": "The CSV is the same records in the same order and the same columns, with two differences in shape: `sources` is an array, so it is flattened into sourceCount and a name/url pair per source (the corpus's maximum is 3); and `country` is a list of keys, written into one cell joined with \"; \". It is RFC 4180 — comma-separated, CRLF, quotes doubled inside quoted fields — encoded UTF-8 with a byte-order mark, which is what makes a spreadsheet read the Cyrillic correctly. A `null` year is an empty cell there. Use the JSON if you want the sources as a list.", "ru": "В CSV те же записи в том же порядке и те же колонки, с двумя отличиями по форме: `sources` — массив, поэтому он разложен на sourceCount и пару «имя/адрес» на каждый источник (максимум по корпусу — 3); а `country` — список ключей, записанный в одну ячейку через «; ». Формат — RFC 4180: разделитель-запятая, перевод строки CRLF, кавычки внутри поля удваиваются; кодировка UTF-8 с меткой порядка байтов, именно она заставляет табличный редактор правильно прочитать кириллицу. Год `null` там — пустая ячейка. Если источники нужны списком, берите JSON." }, "distribution": { "en": "The `bytes` of the JSON release is `null` because a file cannot state its own length without changing it. The CSV's length is exact and is measured before this envelope is serialised.", "ru": "Поле `bytes` у JSON-релиза равно `null`, потому что файл не может назвать собственную длину, не изменив её. Длина CSV точна: она измеряется до сериализации этого конверта." } }, "fields": { "id": { "type": "integer", "en": "Record number, 1 to the record count, contiguous. This is the site's own call number, the anchor a link lands on, and the key to join on.", "ru": "Номер записи, от 1 до числа записей, без пропусков. Это собственный номер сайта, якорь, на который ведёт ссылка, и ключ для соединения таблиц." }, "catalogId": { "type": "integer", "en": "The source catalogue's own number: 1 to 307 with eight gaps, where the gaps are the eight records the source audit removed. It is NOT interchangeable with `id` — see notes.identifiers.", "ru": "Собственный номер исходного каталога: от 1 до 307 с восемью пропусками, и пропуски — это те восемь записей, которые снял аудит. С `id` он не взаимозаменяем — см. notes.identifiers." }, "slug": { "type": "string", "en": "Ascii, kebab-case, unique. The record's stable name inside the corpus.", "ru": "ASCII, через дефис, уникально. Устойчивое имя записи внутри корпуса." }, "url": { "type": "string", "derived": true, "en": "The record on the site: the English register, anchored at this record. The Russian mirror is the same anchor under /ru/ — see notes.links.", "ru": "Запись на сайте: английский реестр с якорем на этой записи. Русское зеркало — тот же якорь с префиксом /ru/, см. notes.links." }, "nameRu": { "type": "string", "en": "What the case is called, in Russian.", "ru": "Название кейса по-русски." }, "nameEn": { "type": "string", "en": "What the case is called, in English.", "ru": "Название кейса по-английски." }, "operatorRu": { "type": "string", "en": "Who runs it, in Russian. Empty where the source names no operator — most of those are peer-reviewed studies, which have none.", "ru": "Кто ведёт кейс, по-русски. Пусто там, где источник оператора не называет: в большинстве таких записей источник — рецензируемое исследование, у которого оператора нет." }, "operatorEn": { "type": "string", "en": "Who runs it, in English.", "ru": "Кто ведёт кейс, по-английски." }, "countryRu": { "type": "string", "en": "The record's countries as the Russian page prints them: the labels of its `country` keys, comma-separated, and — where the record's place within the country is known — that place in parentheses («Франция (Лион)», «Китай (Гонконг)»). Derived from `country` and the place, never typed.", "ru": "Страны записи так, как их печатает русская страница: названия ключей из `country` через запятую, а если известно место внутри страны — это место в скобках («Франция (Лион)», «Китай (Гонконг)»). Выводится из `country` и места и руками не набирается." }, "countryEn": { "type": "string", "en": "The record's countries as the English page prints them, with the same place in parentheses where `countryRu` has one. Derived from `country` and the place.", "ru": "Страны записи так, как их печатает английская страница, с тем же местом в скобках, где оно есть в `countryRu`. Выводится из `country` и места." }, "domain": { "type": "facet key", "en": "Vineyard, cellar or business. A key into facets.domain.", "ru": "Виноградник, погреб или бизнес. Ключ из facets.domain." }, "tech": { "type": "facet key", "en": "The technology class. A key into facets.tech, and not the same field as `techRu`/`techEn`, which are prose.", "ru": "Класс технологии. Ключ из facets.tech; это не то же поле, что `techRu`/`techEn`, — те содержат текст." }, "stage": { "type": "facet key", "en": "Maturity: where the case stands, not how good it is. A key into facets.stage. `unconfirmed` is not a point on that ladder but the absence of one — the record's own sources do not establish a stage.", "ru": "Зрелость: где кейс находится, а не насколько он хорош. Ключ из facets.stage. `unconfirmed` — не точка на шкале, а её отсутствие: источники записи стадию не подтверждают." }, "country": { "type": "array of facet keys", "en": "Where the case runs: one or more keys into facets.country — lower-case ISO 3166-1 alpha-2 codes — or `international` alone, for a platform offered worldwide whose sources name no country of deployment. A case in several countries carries each of them, so a facet count is the number of records INVOLVING a country and the counts sum to more than the record count. In the CSV the list is joined with \"; \".", "ru": "Где работает кейс: один или несколько ключей из facets.country — коды ISO 3166-1 alpha-2 строчными буквами — либо один `international` («Весь мир»), если это платформа, предлагаемая по всему миру, и источники не называют страну внедрения. У кейса, работающего в нескольких странах, указана каждая из них, поэтому счётчик фасета — это число записей, В КОТОРЫХ участвует страна, и в сумме счётчики больше числа записей. В CSV список соединён через «; »." }, "confidence": { "type": "facet key", "en": "How strong the SOURCE is — A, B, C or not stated. A key into facets.confidence. It rates the source and not the case: neither A nor B means verified.", "ru": "Насколько силён ИСТОЧНИК — A, B, C или не указан. Ключ из facets.confidence. Это оценка источника, а не кейса: ни A, ни B не означают «проверено»." }, "aiKind": { "type": "enum: yes | borderline | adjacent", "en": "Whether the record is an AI case proper, a borderline one, or an adjacent technology with no AI component. Deliberately not a facet — see notes.aiKind.", "ru": "Собственно ИИ-кейс, пограничный кейс или смежная технология без ИИ-компонента. Намеренно не фасет — см. notes.aiKind." }, "techRu": { "type": "string", "en": "The technology as the source describes it, in Russian. Empty on the records whose source section carries no technology column.", "ru": "Технология так, как её описывает источник, по-русски. Пусто в записях, у раздела-источника которых нет колонки технологии." }, "techEn": { "type": "string", "en": "The technology as the source describes it, in English.", "ru": "Технология так, как её описывает источник, по-английски." }, "doesRu": { "type": "string", "en": "What the system does, in Russian. The one field every record fills.", "ru": "Что система делает, по-русски. Единственное поле, заполненное у каждой записи." }, "doesEn": { "type": "string", "en": "What the system does, in English.", "ru": "Что система делает, по-английски." }, "resultsRu": { "type": "string", "en": "What the source reports came of it, in Russian.", "ru": "Что, по сообщению источника, из этого вышло, по-русски." }, "resultsEn": { "type": "string", "en": "What the source reports came of it, in English.", "ru": "Что, по сообщению источника, из этого вышло, по-английски." }, "caveatRu": { "type": "string", "en": "A reservation about what the cited source supports, in Russian, on the records that carry one. It states what that source does NOT support, or how the source itself qualifies what it reports, and it is a statement about the source rather than a mark against the case.", "ru": "Оговорка о том, что подтверждает цитируемый источник, по-русски, у тех записей, где она есть. Она говорит, чего источник НЕ подтверждает или какой оговоркой сам источник сопровождает то, что сообщает, и относится к источнику, а не к кейсу." }, "caveatEn": { "type": "string", "en": "A reservation about what the cited source supports, in English.", "ru": "Оговорка о том, что подтверждает цитируемый источник, по-английски." }, "whyRu": { "type": "string", "en": "Why a borderline or adjacent record was classified the way it was, in Russian. Present on the records whose `aiKind` is not `yes`.", "ru": "Почему пограничная или смежная запись отнесена именно так, по-русски. Есть у записей, чей `aiKind` не равен `yes`." }, "whyEn": { "type": "string", "en": "Why a borderline or adjacent record was classified the way it was, in English.", "ru": "Почему пограничная или смежная запись отнесена именно так, по-английски." }, "dataRu": { "type": "string", "en": "The dataset the source names, in Russian, where it names one.", "ru": "Набор данных, если источник его называет, по-русски." }, "dataEn": { "type": "string", "en": "The dataset the source names, in English.", "ru": "Набор данных, если источник его называет, по-английски." }, "yearStart": { "type": "integer or null", "en": "First year the source establishes. `null` where it establishes none, which is a fact about the source and not a hole in the record.", "ru": "Первый год, который устанавливает источник. `null`, если он не устанавливает никакого: это факт об источнике, а не пробел в записи." }, "yearEnd": { "type": "integer or null", "en": "Last year the source establishes, or `null`.", "ru": "Последний год, который устанавливает источник, или `null`." }, "yearDisplay": { "type": "string", "en": "The years as the site prints them, range dash and all. Never empty — a record with no year prints an em dash.", "ru": "Годы в том виде, в каком их печатает сайт, вместе с тире диапазона. Никогда не пусто: у записи без года стоит длинное тире." }, "yearRaw": { "type": "string", "en": "The source's own cell, kept because a handful of them normalise lossily — a month, a decade, a journal issue.", "ru": "Исходная ячейка как есть: сохранена потому, что часть из них нормализуется с потерей — месяц, десятилетие, номер журнала." }, "sectionKey": { "type": "string", "en": "The research section the record was filed under. Filing, not geography: `country` is the geography.", "ru": "Раздел исследования, в котором запись заведена. Это картотека, а не география: география — в поле `country`." }, "sectionRu": { "type": "string", "en": "That section's own title. Russian only, and deliberately: the sections are the research document's own headings, and the document is not published in translation.", "ru": "Название этого раздела. Только по-русски, и намеренно: разделы — это заголовки самого исследовательского документа, а он в переводе не публикуется." }, "sources": { "type": "array of { name, url }", "en": "Where the record comes from. Every record carries at least one, and every URL is a resolvable http(s) address — that is the third of the three conditions a case had to meet. In the CSV this one field is flattened into sourceCount and a name/url pair per source; see notes.csv.", "ru": "Откуда взята запись. У каждой записи есть хотя бы один источник, и каждый URL — рабочий http(s)-адрес: это третье из трёх условий отбора кейса. В CSV это поле разложено на sourceCount и пару «имя/адрес» на каждый источник, см. notes.csv." } }, "facets": { "domain": [ { "key": "viticulture", "ru": "Виноградарство", "en": "Viticulture", "count": 177 }, { "key": "winemaking", "ru": "Виноделие и лаборатория", "en": "Winemaking and laboratory", "count": 47 }, { "key": "business", "ru": "Винный бизнес, маркетинг, гостеприимство", "en": "Wine business, marketing, hospitality", "count": 75 } ], "stage": [ { "key": "research", "ru": "Исследование", "en": "Research", "count": 83 }, { "key": "pilot", "ru": "Пилот", "en": "Pilot", "count": 54 }, { "key": "commercial", "ru": "Коммерческая эксплуатация", "en": "Commercial operation", "count": 129 }, { "key": "scaled", "ru": "Масштабировано", "en": "Scaled", "count": 18 }, { "key": "ended", "ru": "Закрыто, поглощено или свёрнуто", "en": "Closed, acquired or wound down", "count": 11 }, { "key": "unconfirmed", "ru": "Стадия не установлена", "en": "Stage not established", "count": 4 } ], "country": [ { "key": "us", "ru": "США", "en": "United States", "count": 71 }, { "key": "fr", "ru": "Франция", "en": "France", "count": 45 }, { "key": "it", "ru": "Италия", "en": "Italy", "count": 27 }, { "key": "au", "ru": "Австралия", "en": "Australia", "count": 24 }, { "key": "es", "ru": "Испания", "en": "Spain", "count": 24 }, { "key": "cn", "ru": "Китай", "en": "China", "count": 21 }, { "key": "de", "ru": "Германия", "en": "Germany", "count": 18 }, { "key": "pt", "ru": "Португалия", "en": "Portugal", "count": 16 }, { "key": "gb", "ru": "Великобритания", "en": "United Kingdom", "count": 16 }, { "key": "nz", "ru": "Новая Зеландия", "en": "New Zealand", "count": 15 }, { "key": "za", "ru": "ЮАР", "en": "South Africa", "count": 11 }, { "key": "cl", "ru": "Чили", "en": "Chile", "count": 8 }, { "key": "ru", "ru": "Россия", "en": "Russia", "count": 7 }, { "key": "ch", "ru": "Швейцария", "en": "Switzerland", "count": 6 }, { "key": "br", "ru": "Бразилия", "en": "Brazil", "count": 5 }, { "key": "in", "ru": "Индия", "en": "India", "count": 5 }, { "key": "jp", "ru": "Япония", "en": "Japan", "count": 5 }, { "key": "ar", "ru": "Аргентина", "en": "Argentina", "count": 4 }, { "key": "ca", "ru": "Канада", "en": "Canada", "count": 4 }, { "key": "il", "ru": "Израиль", "en": "Israel", "count": 3 }, { "key": "ro", "ru": "Румыния", "en": "Romania", "count": 3 }, { "key": "at", "ru": "Австрия", "en": "Austria", "count": 2 }, { "key": "be", "ru": "Бельгия", "en": "Belgium", "count": 2 }, { "key": "ge", "ru": "Грузия", "en": "Georgia", "count": 2 }, { "key": "gr", "ru": "Греция", "en": "Greece", "count": 2 }, { "key": "si", "ru": "Словения", "en": "Slovenia", "count": 2 }, { "key": "co", "ru": "Колумбия", "en": "Colombia", "count": 1 }, { "key": "hu", "ru": "Венгрия", "en": "Hungary", "count": 1 }, { "key": "ir", "ru": "Иран", "en": "Iran", "count": 1 }, { "key": "ie", "ru": "Ирландия", "en": "Ireland", "count": 1 }, { "key": "lb", "ru": "Ливан", "en": "Lebanon", "count": 1 }, { "key": "lu", "ru": "Люксембург", "en": "Luxembourg", "count": 1 }, { "key": "mx", "ru": "Мексика", "en": "Mexico", "count": 1 }, { "key": "md", "ru": "Молдова", "en": "Moldova", "count": 1 }, { "key": "nl", "ru": "Нидерланды", "en": "Netherlands", "count": 1 }, { "key": "pe", "ru": "Перу", "en": "Peru", "count": 1 }, { "key": "pl", "ru": "Польша", "en": "Poland", "count": 1 }, { "key": "rs", "ru": "Сербия", "en": "Serbia", "count": 1 }, { "key": "sk", "ru": "Словакия", "en": "Slovakia", "count": 1 }, { "key": "se", "ru": "Швеция", "en": "Sweden", "count": 1 }, { "key": "tr", "ru": "Турция", "en": "Türkiye", "count": 1 }, { "key": "ae", "ru": "ОАЭ", "en": "United Arab Emirates", "count": 1 }, { "key": "international", "ru": "Весь мир", "en": "International", "count": 18 } ], "tech": [ { "key": "cv", "ru": "Компьютерное зрение и глубокое обучение на изображениях", "en": "Computer vision and deep learning on images", "count": 52 }, { "key": "remote-sensing", "ru": "Дистанционное 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"en": "Optimisation, planning, demand forecasting", "count": 27 }, { "key": "breeding", "ru": "Селекция и геномика", "en": "Breeding and genomics", "count": 3 }, { "key": "other", "ru": "Прочее", "en": "Other", "count": 5 } ], "confidence": [ { "key": "a", "ru": "A — рецензируемая публикация, официальный отчёт ЕС/министерства или независимая пресса с цифрами", "en": "A — peer-reviewed publication, official EU/ministry report or independent press with figures", "count": 109 }, { "key": "b", "ru": "B — отраслевая пресса или официальное сообщение компании с проверяемыми деталями", "en": "B — trade press or an official company statement with verifiable details", "count": 110 }, { "key": "c", "ru": "C — маркетинговое заявление вендора без независимого подтверждения", "en": "C — vendor marketing claim without independent confirmation", "count": 61 }, { "key": "unstated", "ru": "не указан (раздел рецензируемой науки)", "en": "not stated (peer-reviewed science section)", "count": 19 } ] }, "flags": { "nonAi": { "field": "aiKind", "ru": "Пограничные и смежные технологии", "en": "Borderline and adjacent technologies", "count": 12, "ids": [ 23, 66, 120, 144, 176, 210, 211, 266, 268, 269, 274, 282 ], "kinds": [ { "key": "borderline", "ru": "Пограничный кейс", "en": "Borderline case", "count": 5, "ids": [ 144, 266, 268, 269, 274 ] }, { "key": "adjacent", "ru": "Смежная технология без ИИ-компонента", "en": "Adjacent technology with no AI component", "count": 7, "ids": [ 23, 66, 120, 176, 210, 211, 282 ] } ] } }, "cases": [ { "id": 1, "catalogId": 1, "slug": "tule-technologies-cropx-1", "url": "https://vinumexmachina.com/casebook/cases/#case-1", "nameRu": "Tule Technologies (→ CropX)", "nameEn": "Tule Technologies (→ CropX)", "operatorRu": "", "operatorEn": "", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "sensors-iot", "stage": "ended", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Сенсоры испаряемости + анализ фото полога", "techEn": "Evaporation sensors + canopy photo analysis", "doesRu": "Оценивает водный стресс лозы и потребность в поливе", "doesEn": "Estimates vine water stress and irrigation need", "resultsRu": "Поглощена CropX в январе 2023 как четвёртое приобретение компании.", "resultsEn": "Acquired by CropX in January 2023 as the company's fourth acquisition.", "caveatRu": "Цитата об окупаемости и названия хозяйств в цитируемом источнике отсутствуют; подтверждено только поглощение CropX.", "caveatEn": "The payback quote and the estate names are absent from the cited source; only the CropX acquisition is confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2023, "yearDisplay": "2018–2023", "yearRaw": "2018–2023", "sectionKey": "A1", "sectionRu": "A1. 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США и Канада", "sources": [ { "name": "Ceres.ai", "url": "https://ceres.ai/customer-stories-old/uncovering-irrigation-issues-to-improve-grape-quality" } ] }, { "id": 3, "catalogId": 3, "slug": "gamble-family-vineyards-3", "url": "https://vinumexmachina.com/casebook/cases/#case-3", "nameRu": "Gamble Family Vineyards", "nameEn": "Gamble Family Vineyards", "operatorRu": "Gamble Family Vineyards (Оуквилл)", "operatorEn": "Gamble Family Vineyards (Oakville)", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "Дроны + сеть почвенных датчиков + детекция болезней", "techEn": "Drones + a soil sensor network + disease detection", "doesRu": "Управление поливом и обработками по данным", "doesEn": "Data-driven management of irrigation and treatments", "resultsRu": "«Десятки тысяч галлонов воды на акр» экономии", "resultsEn": "\"Tens of thousands of gallons of water per acre\" saved", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "Fortune", "url": "https://fortune.com/2022/08/23/tech-forward-everyday-ai-california-winemakers/" } ] }, { "id": 4, "catalogId": 4, "slug": "bouchaine-vineyards-cisco-4", "url": "https://vinumexmachina.com/casebook/cases/#case-4", "nameRu": "Bouchaine Vineyards / Cisco", "nameEn": "Bouchaine Vineyards / Cisco", "operatorRu": "Bouchaine Vineyards", "operatorEn": "Bouchaine Vineyards", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "IoT-сеть погодных и почвенных датчиков", "techEn": "IoT network of weather and soil sensors", "doesRu": "Замена визуальной оценки состояния участков на телеметрию", "doesEn": "Replaces visual assessment of block condition with telemetry", "resultsRu": "87 акров под датчиками; система расширена после пилота.", "resultsEn": "87 acres under sensors; the system was extended after the pilot.", "caveatRu": "Источник описывает развёртывание как экспериментальную «живую лабораторию» 2020 года, позже расширенную.", "caveatEn": "The source describes the deployment as an experimental \"living laboratory\" of 2020, later extended.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "Ambrook", "url": "https://ambrook.com/offrange/technology/vineyard-tech-napa-valley-precision-agriculture-monarch" } ] }, { "id": 5, "catalogId": 5, "slug": "monarch-tractor-mk-v-5", "url": "https://vinumexmachina.com/casebook/cases/#case-5", "nameRu": "Monarch Tractor MK-V", "nameEn": "Monarch Tractor MK-V", "operatorRu": "Wente Vineyards, Crocker & Starr, Constellation Brands", "operatorEn": "Wente Vineyards, Crocker & Starr, Constellation Brands", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "robotics", "stage": "ended", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Электрический трактор с опциональной автономностью + платформа Scout", "techEn": "Electric tractor with optional autonomy + the Scout platform", "doesRu": "Автономные работы в междурядьях и построчный сбор данных", "doesEn": "Autonomous inter-row operations and row-by-row data collection", "resultsRu": "Более $240 млн привлечено; 500+ машин; 130 000+ часов наработки. В конце 2025 компания сократила персонал и к апрелю 2026 закрылась; технологию, по данным отраслевых СМИ, купила Caterpillar.", "resultsEn": "More than $240m raised; 500+ machines; 130,000+ operating hours. The company laid off staff in late 2025 and had shut down by April 2026; the technology was sold, reportedly to Caterpillar.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2026, "yearDisplay": "2019–2026", "yearRaw": "2019–2026", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/exclusive-monarch-tractor-ceo-we-should-have-pivoted-harder-and-faster" }, { "name": "Future Farming", "url": "https://www.futurefarming.com/tech-in-focus/autonomous-semi-autosteering-systems/caterpillar-acquires-monarch-technology-after-electric-tractor-startup-shuts-down/" }, { "name": "Farm Progress", "url": "https://web.archive.org/web/20260501183530/https://www.farmprogress.com/max-armstrong/monarch-tractor-shuts-down-what-went-wrong-with-the-500m-electric-tractor-startup" } ] }, { "id": 6, "catalogId": 6, "slug": "guss-automation-john-deere-6", "url": "https://vinumexmachina.com/casebook/cases/#case-6", "nameRu": "GUSS Automation (→ John Deere)", "nameEn": "GUSS Automation (→ John Deere)", "operatorRu": "Виноградники и сады Калифорнии", "operatorEn": "California vineyards and orchards", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "robotics", "stage": "ended", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономные опрыскиватели с GPS и LiDAR", "techEn": "Autonomous sprayers with GPS and LiDAR", "doesRu": "Один оператор ведёт до восьми машин удалённо", "doesEn": "One operator runs up to eight machines remotely", "resultsRu": "250+ машин по миру; 2,6 млн акров обработано; 500 000+ часов автономной работы; полностью куплена John Deere в августе 2025.", "resultsEn": "250+ machines worldwide; 2.6m acres treated; 500,000+ hours of autonomous operation; fully acquired by John Deere in August 2025.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2025, "yearDisplay": "2018–2025", "yearRaw": "2018–2025", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/john-deere-makes-another-high-value-crop-automation-play-with-guss-acquisition" } ] }, { "id": 7, "catalogId": 7, "slug": "saga-robotics-thorvald-uv-c-7", "url": "https://vinumexmachina.com/casebook/cases/#case-7", "nameRu": "Saga Robotics Thorvald (UV-C)", "nameEn": "Saga Robotics Thorvald (UV-C)", "operatorRu": "Castoro Cellars, Bien Nacido Estate, Bonterra Organic Estates", "operatorEn": "Castoro Cellars, Bien Nacido Estate, Bonterra Organic Estates", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономный робот с ультрафиолетовыми лампами", "techEn": "Autonomous robot with ultraviolet lamps", "doesRu": "Ночная обработка УФ-С против оидиума и ботритиса без фунгицидов", "doesEn": "Night-time UV-C treatment against powdery mildew and botrytis without fungicides", "resultsRu": "600 органических акров у Castoro Cellars и пилот Bonterra на 200 акрах с шестью роботами; сокращение химобработок на 60–90%", "resultsEn": "600 organic acres at Castoro Cellars and a Bonterra pilot on 200 acres with six robots; chemical treatments cut by 60–90%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2026, "yearDisplay": "2016–2026", "yearRaw": "2016–2026", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/castoro-cellars-deploys-saga-robotics-uv-c-bots-across-600-organic-acres" } ] }, { "id": 8, "catalogId": 8, "slug": "bloomfield-robotics-scout-kubota-8", "url": "https://vinumexmachina.com/casebook/cases/#case-8", "nameRu": "Bloomfield Robotics «Scout» (→ Kubota)", "nameEn": "Bloomfield Robotics \"Scout\" (→ Kubota)", "operatorRu": "Виноградник в штате Нью-Йорк (пилот)", "operatorEn": "A vineyard in New York State (pilot)", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "cv", "stage": "ended", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "Компьютерное зрение попиксельного анализа растений", "techEn": "Computer vision with per-pixel plant analysis", "doesRu": "Размер и число гроздей, цвет, признаки болезни и зрелости", "doesEn": "Bunch size and count, colour, signs of disease and ripeness", "resultsRu": "Куплена Kubota в 2024; после поглощения фокус сместился в сторону голубики.", "resultsEn": "Acquired by Kubota in 2024; after the acquisition the focus shifted toward blueberries.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2024, "yearDisplay": "2018–2024", "yearRaw": "2018–2024", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "CMU", "url": "https://magazine.cs.cmu.edu/bloomfield-robotics" } ] }, { "id": 9, "catalogId": 9, "slug": "phytopatholobot-cornell-9", "url": "https://vinumexmachina.com/casebook/cases/#case-9", "nameRu": "PhytoPatholoBot (Cornell)", "nameEn": "PhytoPatholoBot (Cornell)", "operatorRu": "Cornell AgriTech + коммерческие виноградники в 6 штатах", "operatorEn": "Cornell AgriTech + commercial vineyards in 6 states", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономный наземный робот + CV + данные NASA", "techEn": "Autonomous ground robot + CV + NASA data", "doesRu": "Карта типа, локализации и тяжести болезни почти в реальном времени", "doesEn": "Near-real-time map of disease type, location and severity", "resultsRu": "Качество детекции «сопоставимо с опытными скаутами»; финансирование USDA NIFA и NASA JPL.", "resultsEn": "Detection quality \"comparable to experienced scouts\"; funding from USDA NIFA and NASA JPL.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "Cornell Chronicle", "url": "https://news.cornell.edu/stories/2025/09/robot-matches-humans-scouting-vineyard-diseases" } ] }, { "id": 10, "catalogId": 10, "slug": "model-urozhaya-cornell-random-forest-10", "url": "https://vinumexmachina.com/casebook/cases/#case-10", "nameRu": "Модель урожая INRAE / Cornell (Random Forest)", "nameEn": "INRAE / Cornell yield model (Random Forest)", "operatorRu": "CLEREL, AVA Lake Erie", "operatorEn": "CLEREL, AVA Lake Erie", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "yield", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Random Forest по данным вигора до цветения", "techEn": "Random Forest on pre-flowering vigour data", "doesRu": "Прогноз урожая и массы обрезки", "doesEn": "Yield and pruning-weight forecast", "resultsRu": "Ошибка прогноза урожая 2–8%; массы обрезки — 15–20%; 321 точка отбора, 2018–2021", "resultsEn": "Yield forecast error 2–8%; pruning weight 15–20%; 321 sampling points, 2018–2021", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "A1", "sectionRu": "A1. 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США и Канада", "sources": [ { "name": "Wine Industry Advisor", "url": "https://wineindustryadvisor.com/2025/12/03/worlds-first-on-farm-robotics-and-automation-hub-comes-to-sonoma-county/" } ] }, { "id": 13, "catalogId": 13, "slug": "e-j-gallo-gis-prilozhenie-13", "url": "https://vinumexmachina.com/casebook/cases/#case-13", "nameRu": "E&J Gallo GIS-приложение", "nameEn": "E&J Gallo GIS application", "operatorRu": "E&J Gallo (внутренний инструмент)", "operatorEn": "E&J Gallo (internal tool)", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "Спутниковые снимки + ГИС + полевые данные", "techEn": "Satellite imagery + GIS + field data", "doesRu": "Оценка зрелости и планирование сбора циклами 7–14 дней", "doesEn": "Ripeness assessment and harvest planning in 7–14 day cycles", "resultsRu": "Три года разработки с 2014", "resultsEn": "Three years of development from 2014", "caveatRu": "На 2017 год интеграция со спутниковыми снимками и ГИС была планом на два-три года вперёд; работало само приложение планирования сбора.", "caveatEn": "As of 2017 the integration with satellite imagery and GIS was a plan two to three years ahead; what was working was the harvest-planning application itself.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2017, "yearDisplay": "2017", "yearRaw": "2017", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "CIO.com", "url": "https://www.cio.com/article/230368/e-j-gallo-deploys-data-driven-app-to-harvest-a-better-grape.html" } ] }, { "id": 14, "catalogId": 14, "slug": "vinsight-14", "url": "https://vinumexmachina.com/casebook/cases/#case-14", "nameRu": "Vinsight", "nameEn": "Vinsight", "operatorRu": "Крупные калифорнийские винодельни", "operatorEn": "Large Californian wineries", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "yield", "stage": "unconfirmed", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Landsat/Terra/Aqua + ML по десятилетию урожаев", "techEn": "Landsat/Terra/Aqua + ML on a decade of harvests", "doesRu": "Прогноз урожая за ~4 месяца до сбора", "doesEn": "Yield forecast ~4 months before harvest", "resultsRu": "По заявлению компании, средняя ошибка прогноза — 10% против 30–40% отраслевого стандарта; $250 000 seed. Текущий статус неясен.", "resultsEn": "According to the company, mean forecast error is 10% against the industry standard of 30–40%; $250,000 seed. Current status unclear.", "caveatRu": "Точность заявлена самой компанией и независимо не подтверждена; статус компании на 2026 год неизвестен.", "caveatEn": "The accuracy is claimed by the company itself and is not independently confirmed; the company's status as of 2026 is unknown.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2017, "yearDisplay": "≈2017", "yearRaw": "~2017", "sectionKey": "A1", "sectionRu": "A1. 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США и Канада", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/semios-raises-100m-to-scale-precision-ag-platform-with-more-acquisitions-likely" } ] }, { "id": 17, "catalogId": 17, "slug": "biome-makers-becrop-17", "url": "https://vinumexmachina.com/casebook/cases/#case-17", "nameRu": "Biome Makers BeCrop", "nameEn": "Biome Makers BeCrop", "operatorRu": "Сельхозпроизводители разных культур", "operatorEn": "Growers of various crops", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "chemometrics", "stage": "commercial", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "ДНК-секвенирование почвы + ML", "techEn": "Soil DNA sequencing + ML", "doesRu": "Оценка здоровья почвы по микробиому", "doesEn": "Soil health assessment from the microbiome", "resultsRu": "$15 млн Series B под руководством Prosus Ventures", "resultsEn": "$15m Series B led by Prosus Ventures", "caveatRu": "Из показателей компании цитируемым источником подтверждён только раунд $15 млн.", "caveatEn": "Of the company's figures, only the $15m round is confirmed by the cited source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2021, "yearDisplay": "2016–2021", "yearRaw": "2016–2021", "sectionKey": "A1", "sectionRu": "A1. 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США и Канада", "sources": [ { "name": "Forbes", "url": "https://www.forbes.com/sites/jillbarth/2024/02/23/how-ai-helps-winemakers-understand-what-people-taste/" } ] }, { "id": 21, "catalogId": 21, "slug": "cladisiq-21", "url": "https://vinumexmachina.com/casebook/cases/#case-21", "nameRu": "CladisIQ", "nameEn": "CladisIQ", "operatorRu": "Винодельни долины Напа", "operatorEn": "Napa Valley wineries", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Сеть сенсоров + AI", "techEn": "Sensor network + AI", "doesRu": "Гиперлокальные данные о дыме и качестве воздуха при пожарах", "doesEn": "Hyperlocal smoke and air-quality data during fires", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "Wine Industry Insight", "url": "https://www.wineindustryinsight.com/p/change-at-top-of-jackson-family-wines-cladisiq-deploys-ai-powered-sensors-to-help-napa-wineries-fire" } ] }, { "id": 22, "catalogId": 22, "slug": "carbon-robotics-laserweeder-22", "url": "https://vinumexmachina.com/casebook/cases/#case-22", "nameRu": "Carbon Robotics LaserWeeder", "nameEn": "Carbon Robotics LaserWeeder", "operatorRu": "Общая агрокультура (виноград не подтверждён)", "operatorEn": "General agriculture (grapes not confirmed)", "countryRu": "США, Австралия, Великобритания, Канада", "countryEn": "United States, Australia, United Kingdom, Canada", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "us", "au", "gb", "ca" ], "confidence": "b", "aiKind": "yes", "techRu": "Лазерная прополка под управлением ИИ", "techEn": "AI-controlled laser weeding", "doesRu": "Уничтожение сорняков без химии и обработки почвы", "doesEn": "Kills weeds without chemicals or soil cultivation", "resultsRu": "$70 млн раунд; инвестиции венчурного подразделения NVIDIA", "resultsEn": "$70m round; investment from NVIDIA's venture arm", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/carbon-robotics-eyes-new-regions-products-with-70m-raise-were-focused-very-intently-on-the-field" } ] }, { "id": 23, "catalogId": 23, "slug": "brock-ccovi-vinealert-23", "url": "https://vinumexmachina.com/casebook/cases/#case-23", "nameRu": "Brock CCOVI VineAlert", "nameEn": "Brock CCOVI VineAlert", "operatorRu": "Виноградари Ниагары (Канада)", "operatorEn": "Niagara grape growers (Canada)", "countryRu": "Канада", "countryEn": "Canada", "domain": "viticulture", "tech": "disease-weather", "stage": "unconfirmed", "country": [ "ca" ], "confidence": "c", "aiKind": "adjacent", "techRu": "Мониторинг морозостойкости почек", "techEn": "Bud cold-hardiness monitoring", "doesRu": "Оповещения о риске зимнего повреждения", "doesEn": "Alerts on the risk of winter damage", "resultsRu": "Методология ML в открытых материалах не описана.", "resultsEn": "No ML methodology is described in the public materials.", "caveatRu": "Стадия зрелости цитируемым источником не подтверждается.", "caveatEn": "The maturity stage is not confirmed by the cited source.", "whyRu": "Дифференциальный термический анализ морозостойкости почек в программируемых камерах. Физическое измерение без предсказательной модели.", "whyEn": "Differential thermal analysis of bud cold hardiness in programmable chambers. A physical measurement with no predictive model.", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A1", "sectionRu": "A1. США и Канада", "sources": [ { "name": "CCOVI", "url": "https://brocku.ca/ccovi/" } ] }, { "id": 24, "catalogId": 25, "slug": "naio-technologies-ted-oz-jo-orio-24", "url": "https://vinumexmachina.com/casebook/cases/#case-24", "nameRu": "Naïo Technologies (Ted, Oz, Jo, Orio)", "nameEn": "Naïo Technologies (Ted, Oz, Jo, Orio)", "operatorRu": "Виноградники Франции и ещё 20+ стран", "operatorEn": "Vineyards in France and 20+ other countries", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономные роботы для механической прополки", "techEn": "Autonomous robots for mechanical weeding", "doesRu": "Замена гербицидов механической обработкой", "doesEn": "Replaces herbicides with mechanical cultivation", "resultsRu": "350 машин в эксплуатации; процедура банкротства в июне 2025, спасена пакетом €6,4 млн от Mirova, Bpifrance и региона Окситания; штат сокращён с 80 до 21; цель — 100 роботов в год к 2028.", "resultsEn": "350 machines in service; insolvency proceedings in June 2025, rescued by a €6.4m package from Mirova, Bpifrance and the Occitanie region; headcount cut from 80 to 21; target 100 robots a year by 2028.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2011, "yearEnd": 2025, "yearDisplay": "2011–2025", "yearRaw": "2011–2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Gazette du Midi", "url": "https://gazette-du-midi.fr/au-sommaire/entreprises/robots-agricoles-avec-le-soutien-de-la-region-naio-technologies-trouve-un" }, { "name": "AgFunderNews", "url": "https://agfundernews.com/ag-robotics-startup-naio-bounces-back-after-a-year-of-financial-turmoil" } ] }, { "id": 25, "catalogId": 26, "slug": "vitibot-bakus-25", "url": "https://vinumexmachina.com/casebook/cases/#case-25", "nameRu": "VitiBot Bakus", "nameEn": "VitiBot Bakus", "operatorRu": "CUMA la Meusnoise и CUMA viti-vinicole de Cheverny, Луар и Шер (демонстрация)", "operatorEn": "CUMA la Meusnoise and CUMA viti-vinicole de Cheverny, Loir-et-Cher (demonstration)", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Электрический автономный портальный трактор", "techEn": "Electric autonomous straddle tractor", "doesRu": "Обработка почвы, скашивание", "doesEn": "Soil cultivation, mowing", "resultsRu": "€180 000 против €115 000 за обычный трактор с водителем; та же стоимость часа (€80) при 440 моточасах в год, что у трактора при 350, без учёта субсидии 55% для кооперативов CUMA по схеме PCAE; RTK-подписка и обслуживание €4 800/год", "resultsEn": "€180,000 against €115,000 for a conventional tractor with a driver; the same cost per hour (€80) at 440 engine hours a year as the tractor at 350, not counting the 55% subsidy for CUMA cooperatives under the PCAE scheme; RTK subscription and maintenance €4,800/year", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "2021", "yearRaw": "2021", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Entraid", "url": "https://www.entraid.com/articles/rentabilite-robot-bakus-vitibot-comparatif-enjambeur" } ] }, { "id": 26, "catalogId": 27, "slug": "wall-ye-26", "url": "https://vinumexmachina.com/casebook/cases/#case-26", "nameRu": "Wall-Ye", "nameEn": "Wall-Ye", "operatorRu": "Хозяйства юга Бургундии", "operatorEn": "Estates in southern Burgundy", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "robotics", "stage": "ended", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Распознавание формы и цвета + роботизированная обрезка", "techEn": "Shape and colour recognition + robotic pruning", "doesRu": "Обрезка, пасынкование, опрыскивание", "doesEn": "Pruning, de-suckering, spraying", "resultsRu": "~30 машин продано за всю историю; цена €25 000. Заголовок Vitisphere: робот «завораживает, но разочаровывает».", "resultsEn": "~30 machines sold in its entire history; price €25,000. Vitisphere headline: the robot \"fascinates but disappoints\".", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2019, "yearDisplay": "2016–2019", "yearRaw": "2016–2019", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Agrotic", "url": "https://www.agrotic.org/les-actualites/les-robots-viticoles-francais/" } ] }, { "id": 27, "catalogId": 28, "slug": "vitirover-27", "url": "https://vinumexmachina.com/casebook/cases/#case-27", "nameRu": "Vitirover", "nameEn": "Vitirover", "operatorRu": "Виноградники Бордо, солнечные фермы Endesa", "operatorEn": "Bordeaux vineyards, Endesa solar farms", "countryRu": "Франция, Испания", "countryEn": "France, Spain", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "fr", "es" ], "confidence": "b", "aiKind": "yes", "techRu": "Автономная газонокосилка на солнечных батареях", "techEn": "Solar-powered autonomous mower", "doesRu": "Скашивание травы в междурядьях как сервис, а не продажа техники", "doesEn": "Mowing the grass between the rows as a service rather than a machine sale", "resultsRu": "100 роботов к концу 2021, цель 200 машин к концу 2022; ~1 робот на гектар; вес 20 кг; скорость 200 м/час", "resultsEn": "100 robots by the end of 2021, target 200 machines by the end of 2022; ~1 robot per hectare; weight 20 kg; speed 200 m/hour", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2026, "yearDisplay": "2021–2026", "yearRaw": "2021–2026", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Révolution Énergétique", "url": "https://www.revolution-energetique.com/actus/que-devient-le-robot-tondeur-electrique-solaire-autonome-vitirover/" } ] }, { "id": 28, "catalogId": 29, "slug": "chouette-28", "url": "https://vinumexmachina.com/casebook/cases/#case-28", "nameRu": "Chouette", "nameEn": "Chouette", "operatorRu": "~100 хозяйств", "operatorEn": "~100 estates", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "cv", "stage": "commercial", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Компьютерное зрение на дронах и тракторных сенсорах", "techEn": "Computer vision on drones and tractor sensors", "doesRu": "Детекция болезней (пятна милдью от 0,5 см), созревание, оценка урожая, карты дифференцированной обработки", "doesEn": "Disease detection (downy mildew spots from 0.5 cm), ripening, yield assessment, variable-rate treatment maps", "resultsRu": "€5 млн Series A в 2023", "resultsEn": "€5m Series A in 2023", "caveatRu": "Основной источник закрыт robots.txt; €5 млн и ~100 хозяйств подтверждены по другому источнику.", "caveatEn": "The main source is blocked by robots.txt; the €5m and the ~100 estates are confirmed from another source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2015, "yearEnd": 2025, "yearDisplay": "2015–2025", "yearRaw": "2015–2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "L'Usine Digitale", "url": "https://www.usine-digitale.fr/article/chouette-l-agritech-qui-aide-les-viticulteurs-a-surveiller-et-a-traiter-leurs-vignes-leve-5-millions-d-euros.N2098361" } ] }, { "id": 29, "catalogId": 30, "slug": "vitidrone-29", "url": "https://vinumexmachina.com/casebook/cases/#case-29", "nameRu": "Vitidrone", "nameEn": "Vitidrone", "operatorRu": "Château Le Bon Pasteur, Clos L'Apogée (Помроль, Сент-Эмильон)", "operatorEn": "Château Le Bon Pasteur, Clos L'Apogée (Pomerol, Saint-Émilion)", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "remote-sensing", "stage": "pilot", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Дрон + цифровой двойник геопривязанных лоз", "techEn": "Drone + digital twin of geolocated vines", "doesRu": "Ранняя детекция болезней на уровне отдельного растения", "doesEn": "Early disease detection at the level of the individual plant", "resultsRu": "~2 га за полёт 40 минут; инкубация Inria Start-Up Studio; коммерческий запуск намечен на конец 2026.", "resultsEn": "~2 ha per 40-minute flight; incubation at Inria Start-Up Studio; commercial launch planned for the end of 2026.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2026, "yearDisplay": "2024–2026", "yearRaw": "2024–2026", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Bouger à Bordeaux", "url": "https://www.bougerabordeaux.com/actu/news/cette-start-up-bordelaise-veut-detecter-les-maladies-de-la-vigne-grace-a-lia/" } ] }, { "id": 30, "catalogId": 31, "slug": "greenshield-vinemapper-30", "url": "https://vinumexmachina.com/casebook/cases/#case-30", "nameRu": "Greenshield / VineMapper", "nameEn": "Greenshield / VineMapper", "operatorRu": "Подписчики сервиса", "operatorEn": "Service subscribers", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "cv", "stage": "ended", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Тракторное зрение в видимом диапазоне", "techEn": "Tractor-mounted vision in the visible band", "doesRu": "Картирование очагов милдью в реальном времени", "doesEn": "Real-time mapping of downy mildew foci", "resultsRu": "€15 000 покупка или €3 000/год аренда + €700–800/год за ИИ-подписку. Судебная ликвидация 27 марта 2025.", "resultsEn": "€15,000 to buy or €3,000/year to rent + €700–800/year for the AI subscription. Judicial liquidation on 27 March 2025.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Réussir Vigne", "url": "https://www.reussir.fr/vigne/de-nouveaux-outils-pour-estimer-le-risque-de-maladies-dans-les-vignes" } ] }, { "id": 31, "catalogId": 32, "slug": "bioscout-sporescout-31", "url": "https://vinumexmachina.com/casebook/cases/#case-31", "nameRu": "BioScout SporeScout", "nameEn": "BioScout SporeScout", "operatorRu": "Французские виноградники (выход на рынок в 2025)", "operatorEn": "French vineyards (market entry in 2025)", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Споровая ловушка с ИИ-анализом изображений", "techEn": "Spore trap with AI image analysis", "doesRu": "Идентификация спор милдью, оидиума, ботритиса и болезней древесины", "doesEn": "Identification of spores of downy mildew, powdery mildew, botrytis and trunk diseases", "resultsRu": "Забор воздуха 10 л/мин; €7 000 в первый год, включая прибор, ПО и обслуживание. Заявления «8 лет НИОКР» и «8 млн калибровочных изображений» опровергаются сайтом самой компании: там сказано «за последние четыре года» и «сотни тысяч» размеченных изображений.", "resultsEn": "Air intake 10 l/min; €7,000 in the first year, including the device, software and servicing. The claims of \"8 years of R&D\" and \"8m calibration images\" are contradicted by the company's own website: it says \"over the past four years\" and \"hundreds of thousands\" of labelled images.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Réussir Vigne", "url": "https://www.reussir.fr/vigne/vinitech-2024-bioscout-capte-et-repere-les-spores-des-pathogenes" }, { "name": "BioScout", "url": "https://www.bioscout.com.au/posts/how-bioscout-works" } ] }, { "id": 32, "catalogId": 33, "slug": "oenoview-groupe-icv-vivelys-32", "url": "https://vinumexmachina.com/casebook/cases/#case-32", "nameRu": "Oenoview (Groupe ICV / Vivelys)", "nameEn": "Oenoview (Groupe ICV / Vivelys)", "operatorRu": "Grands Chais de France, Vignobles de Vendéole, La Vigneronne", "operatorEn": "Grands Chais de France, Vignobles de Vendéole, La Vigneronne", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "remote-sensing", "stage": "scaled", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Спутниковое зондирование SPOT (1,5 м) и Sentinel-2", "techEn": "SPOT satellite sensing (1.5 m) and Sentinel-2", "doesRu": "Карты вигора, водного статуса и неоднородности участка", "doesEn": "Maps of vigour, water status and plot heterogeneity", "resultsRu": "Спутник Sentinel-2 даёт обновление раз в 5 дней.", "resultsEn": "The Sentinel-2 satellite gives an update every 5 days.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "ICV", "url": "https://www.icv.fr/en/viticulture-oenology-consulting/oenoview" } ] }, { "id": 33, "catalogId": 34, "slug": "decitrait-ifv-palaty-selskogo-khozyaystva-33", "url": "https://vinumexmachina.com/casebook/cases/#case-33", "nameRu": "DeciTrait (IFV + палаты сельского хозяйства)", "nameEn": "DeciTrait (IFV + chambers of agriculture)", "operatorRu": "Национальная сеть хозяйств через MesParcelles", "operatorEn": "A national network of estates via MesParcelles", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "disease-weather", "stage": "scaled", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Модельная система поддержки решений", "techEn": "Model-based decision support system", "doesRu": "Риск милдью, оидиума и чёрной гнили в реальном времени", "doesEn": "Real-time risk of downy mildew, powdery mildew and black rot", "resultsRu": "Экономия 200–750 г меди на гектар; снижение индекса пестицидной нагрузки IFT в среднем до 35%", "resultsEn": "Saving of 200-750 g of copper per hectare; reduction of the IFT pesticide-load index by up to 35% on average", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Chambres d'agriculture", "url": "https://chambres-agriculture.fr/etre-accompagne/nos-solutions-numeriques/decitrait" } ] }, { "id": 34, "catalogId": 35, "slug": "sencrop-34", "url": "https://vinumexmachina.com/casebook/cases/#case-34", "nameRu": "Sencrop", "nameEn": "Sencrop", "operatorRu": "20 000+ фермеров и виноградарей в 20+ странах", "operatorEn": "20,000+ farmers and winegrowers in 20+ countries", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "disease-weather", "stage": "scaled", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Подключённые микрометеостанции + предиктивные модели", "techEn": "Connected micro weather stations + predictive models", "doesRu": "Оповещения о риске болезней, заморозках, сроках полива", "doesEn": "Alerts on disease risk, frost and irrigation timing", "resultsRu": "$18 млн Series B в 2022; ~100 сотрудников", "resultsEn": "$18m Series B in 2022; ~100 employees", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2022, "yearDisplay": "2016–2022", "yearRaw": "2016–2022", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Sencrop", "url": "https://fr.blog.sencrop.com/levee-fonds-2022/" } ] }, { "id": 35, "catalogId": 36, "slug": "weenat-35", "url": "https://vinumexmachina.com/casebook/cases/#case-35", "nameRu": "Weenat", "nameEn": "Weenat", "operatorRu": "30 000+ пользователей в 15 странах Европы", "operatorEn": "30,000+ users in 15 European countries", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "disease-weather", "stage": "scaled", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Агросенсоры + ИИ-аналитика полива и защиты", "techEn": "Agricultural sensors + AI analytics for irrigation and crop protection", "doesRu": "Управление поливом и оповещения о милдью", "doesEn": "Irrigation management and downy mildew alerts", "resultsRu": "25 000 датчиков; €8,5 млн Series C в 2024; обрабатывает более 1 млрд точек данных в сутки; потенциал сокращения потребления воды ~20%.", "resultsEn": "25,000 sensors; €8.5m Series C in 2024; processes more than 1bn data points a day; potential water-use reduction of ~20%.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2014, "yearEnd": 2025, "yearDisplay": "2014–2025", "yearRaw": "2014–2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "L'Essentiel de l'Éco", "url": "https://lessentieldeleco.fr/3467-weenat/" } ] }, { "id": 36, "catalogId": 37, "slug": "fruition-sciences-36", "url": "https://vinumexmachina.com/casebook/cases/#case-36", "nameRu": "Fruition Sciences", "nameEn": "Fruition Sciences", "operatorRu": "Ovid Winery", "operatorEn": "Ovid Winery", "countryRu": "США, Франция, Австралия", "countryEn": "United States, France, Australia", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "us", "fr", "au" ], "confidence": "b", "aiKind": "yes", "techRu": "Датчики сокотока + физиологические замеры", "techEn": "Sap-flow sensors + physiological measurements", "doesRu": "Управление поливом по реальному водному статусу лозы", "doesEn": "Irrigation management by the vine's actual water status", "resultsRu": "Работает с 2007; штаб-квартиры в Монпелье и Напе.", "resultsEn": "Operating since 2007; headquarters in Montpellier and Napa.", "caveatRu": "Цитируемый источник подтверждает единственного клиента — Ovid Winery.", "caveatEn": "The cited source confirms a single client, Ovid Winery.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2007, "yearEnd": null, "yearDisplay": "2007–", "yearRaw": "2007–", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Fruition Sciences", "url": "https://fruitionsciences.com" } ] }, { "id": 37, "catalogId": 38, "slug": "sabi-agri-37", "url": "https://vinumexmachina.com/casebook/cases/#case-37", "nameRu": "Sabi Agri", "nameEn": "Sabi Agri", "operatorRu": "Виноградари Франции", "operatorEn": "French winegrowers", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "fr" ], "confidence": "c", "aiKind": "yes", "techRu": "Электрическая портальная и гусеничная техника, робот SRBC", "techEn": "Electric straddle and tracked machinery, SRBC robot", "doesRu": "Междурядные работы на электротяге", "doesEn": "Inter-row work on electric drive", "resultsRu": "Робот SRBC от €13 500; по линейке в целом заявлено 2–3 часа зарядки на 8–10 часов работы и экономия 10,4 т CO₂ в год.", "resultsEn": "SRBC robot from €13,500; for the range as a whole, 2-3 hours of charging for 8-10 hours of operation and a saving of 10.4 t of CO₂ a year are claimed.", "caveatRu": "Время зарядки и экономия CO₂ относятся к линейке машин в целом; привязка к роботу SRBC источником не подтверждена.", "caveatEn": "The charging time and the CO₂ saving relate to the machine range as a whole; a link to the SRBC robot is not confirmed by the source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Sabi Agri", "url": "https://sabi-agri.com" } ] }, { "id": 38, "catalogId": 39, "slug": "trapview-vo-frantsii-38", "url": "https://vinumexmachina.com/casebook/cases/#case-38", "nameRu": "Trapview во Франции", "nameEn": "Trapview in France", "operatorRu": "Французские виноградники", "operatorEn": "French vineyards", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "cv", "stage": "commercial", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Компьютерное зрение в подключённых феромонных ловушках", "techEn": "Computer vision in connected pheromone traps", "doesRu": "Удалённый мониторинг гроздевой листовёртки вместо ручного подсчёта", "doesEn": "Remote monitoring of the European grapevine moth instead of manual counting", "resultsRu": "Более 90% точности по гроздевой листовёртке, около пятидесяти распознаваемых видов", "resultsEn": "More than 90% accuracy on the European grapevine moth, around fifty species recognised", "caveatRu": "Глобальные платформенные цифры к французскому внедрению не привязаны.", "caveatEn": "The global platform figures are not tied to the French deployment.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Vinseo", "url": "https://www.vinseo.com/trapview-la-reconnaissance-dimages-pour-suivre-les-insectes-a-distance/" } ] }, { "id": 39, "catalogId": 40, "slug": "moet-chandon-photobox-39", "url": "https://vinumexmachina.com/casebook/cases/#case-39", "nameRu": "Moët & Chandon «Photobox»", "nameEn": "Moët & Chandon \"Photobox\"", "operatorRu": "Прессовый центр Le Val du Clos, Шампань", "operatorEn": "Le Val du Clos press centre, Champagne", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "fr" ], "confidence": "c", "aiKind": "yes", "techRu": "Глубокое обучение + компьютерное зрение", "techEn": "Deep learning + computer vision", "doesRu": "Автоматический скан винограда на входе: интенсивность окраски пино нуара, гниль", "doesEn": "Automatic scan of grapes on intake: colour intensity of pinot noir, rot", "resultsRu": "Источник описывает работу исследовательского центра; цифр он не приводит.", "resultsEn": "The source describes the work of the research centre; it gives no figures.", "caveatRu": "Развёртывание по всей цепочке приёмки и винификации цитируемым источником не подтверждается.", "caveatEn": "Deployment across the whole intake and vinification chain is not confirmed by the cited source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "CScience", "url": "https://web.archive.org/web/20251119012708/https://www.cscience.ca/pratiques-viticoles-la-revolution-moet-hennessy/" } ] }, { "id": 40, "catalogId": 41, "slug": "yanmar-yv01-40", "url": "https://vinumexmachina.com/casebook/cases/#case-40", "nameRu": "Yanmar YV01", "nameEn": "Yanmar YV01", "operatorRu": "Moët & Chandon, Шампань", "operatorEn": "Moët & Chandon, Champagne", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономный опрыскиватель с RTK-GPS", "techEn": "Autonomous sprayer with RTK-GPS", "doesRu": "Работа на склонах до 45° со скоростью до 4 км/ч", "doesEn": "Work on slopes of up to 45° at speeds of up to 4 km/h", "resultsRu": "Цена около £130 000; прополочный модуль в продаже с января 2024", "resultsEn": "Price around £130,000; weeding module on sale since January 2024", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2024, "yearDisplay": "2019–2024", "yearRaw": "2019–2024", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2024/05/moet-backs-robots-to-manage-vineyards-in-champagne/" } ] }, { "id": 41, "catalogId": 42, "slug": "proekt-diva-41", "url": "https://vinumexmachina.com/casebook/cases/#case-41", "nameRu": "Проект DIVA", "nameEn": "DIVA project", "operatorRu": "CIVC (Шампань), CIVB (Бордо), BIVB (Бургундия), Bernard Magrez, LVMH", "operatorEn": "CIVC (Champagne), CIVB (Bordeaux), BIVB (Burgundy), Bernard Magrez, LVMH", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "remote-sensing", "stage": "research", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "ИИ + мультиспектральная съёмка с дронов", "techEn": "AI + multispectral drone imaging", "doesRu": "Автоматическая детекция золотистого пожелтения, в том числе бессимптомного", "doesEn": "Automatic detection of flavescence dorée, including asymptomatic cases", "resultsRu": "Трёхлетняя аспирантура по механизму CIFRE; межрегиональный отраслевой консорциум", "resultsEn": "A three-year doctorate under the CIFRE scheme; a cross-regional industry consortium", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "GDR IASIS CNRS", "url": "https://gdr-iasis.cnrs.fr/kiosque/these-cifre-diva-disease-identification-in-vineyards-using-ai-general-tool-forvineyard-disease-detection/" } ] }, { "id": 42, "catalogId": 43, "slug": "champagne-henriot-42", "url": "https://vinumexmachina.com/casebook/cases/#case-42", "nameRu": "Champagne Henriot", "nameEn": "Champagne Henriot", "operatorRu": "Champagne Henriot", "operatorEn": "Champagne Henriot", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "cv", "stage": "commercial", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Тракторы с камерами + дроны", "techEn": "Camera-equipped tractors + drones", "doesRu": "Анализ почвы и полога, детекция милдью и эски", "doesEn": "Soil and canopy analysis, detection of downy mildew and esca", "resultsRu": "Органическая сертификация получена в январе 2025; проект Alliance Terroirs с 2020.", "resultsEn": "Organic certification obtained in January 2025; the Alliance Terroirs project since 2020.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2025, "yearDisplay": "2020–2025", "yearRaw": "2020–2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/06/champagne-henriot-utilises-ai-to-drive-viticulture/" } ] }, { "id": 43, "catalogId": 44, "slug": "exapta-43", "url": "https://vinumexmachina.com/casebook/cases/#case-43", "nameRu": "EXAPTA", "nameEn": "EXAPTA", "operatorRu": "Хозяйства Бордо", "operatorEn": "Bordeaux estates", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "optimisation", "stage": "pilot", "country": [ "fr" ], "confidence": "c", "aiKind": "yes", "techRu": "Оптимизационные алгоритмы (платформа BaPCod, Inria)", "techEn": "Optimisation algorithms (BaPCod platform, Inria)", "doesRu": "Составление графика работ по технике, обработкам и персоналу с учётом погоды", "doesEn": "Scheduling of machinery, treatments and staff with the weather taken into account", "resultsRu": "Совместная разработка Ertus Group и Inria/CNRS/Univ. Bordeaux", "resultsEn": "Jointly developed by Ertus Group and Inria/CNRS/Univ. Bordeaux", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2017, "yearDisplay": "2016–2017", "yearRaw": "2016–2017", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Aquitaine Online", "url": "http://www.aquitaineonline.com/actualites-en-aquitaine/economie-industrie/6643-exapta-numerique-grands-crus-bordelais.html" } ] }, { "id": 44, "catalogId": 45, "slug": "pellenc-rx-20-44", "url": "https://vinumexmachina.com/casebook/cases/#case-44", "nameRu": "Pellenc RX-20", "nameEn": "Pellenc RX-20", "operatorRu": "Хозяйства-ранние адоптеры", "operatorEn": "Early-adopter estates", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "robotics", "stage": "pilot", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Автономный гусеничный робот", "techEn": "Autonomous tracked robot", "doesRu": "Междурядные работы", "doesEn": "Inter-row work", "resultsRu": "Стадия первых полевых выходов", "resultsEn": "Stage of first field outings", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Réussir Vigne", "url": "https://www.reussir.fr/vigne/le-robot-rx-20-de-pellenc-fait-ses-premiers-pas-dans-les-vignes" } ] }, { "id": 45, "catalogId": 47, "slug": "agridatavalue-horizon-europe-45", "url": "https://vinumexmachina.com/casebook/cases/#case-45", "nameRu": "AgriDataValue (Horizon Europe)", "nameEn": "AgriDataValue (Horizon Europe)", "operatorRu": "Conseil des Vins de Saint-Émilion (Франция), SIVE (Италия)", "operatorEn": "Conseil des Vins de Saint-Émilion (France), SIVE (Italy)", "countryRu": "Франция, Италия", "countryEn": "France, Italy", "domain": "viticulture", "tech": "sensors-iot", "stage": "research", "country": [ "fr", "it" ], "confidence": "a", "aiKind": "yes", "techRu": "IoT + дроны + спутник + ИИ-аналитика", "techEn": "IoT + drones + satellite + AI analytics", "doesRu": "Мультикультурная платформа умного земледелия с винными пилотами", "doesEn": "Multi-crop smart farming platform with wine pilots", "resultsRu": "€7 145 500, 100% финансирование ЕС. 23 пилота, 181 000 га, 4 200 хозяйств и 89 000 получателей — цели проекта к 2029 году, а не достигнутые показатели.", "resultsEn": "€7,145,500, 100% EU funding. 23 pilots, 181,000 ha, 4,200 estates and 89,000 beneficiaries — the project's targets by 2029, not figures achieved.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2029, "yearDisplay": "2023–2029", "yearRaw": "2023–2029", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "CORDIS", "url": "https://cordis.europa.eu/project/id/101086461" } ] }, { "id": 46, "catalogId": 48, "slug": "paket-generativnogo-ii-46", "url": "https://vinumexmachina.com/casebook/cases/#case-46", "nameRu": "Пакет генеративного ИИ", "nameEn": "Generative AI package", "operatorRu": "Cave coopérative de Lugny (Бургундия)", "operatorEn": "Cave coopérative de Lugny (Burgundy)", "countryRu": "Франция", "countryEn": "France", "domain": "viticulture", "tech": "llm", "stage": "commercial", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "LLM, RPA, аналитика", "techEn": "LLM, RPA, analytics", "doesRu": "Транскрипция совещаний, генерация HACCP-обучения, авторазметка фото, аналитика продаж", "doesEn": "Meeting transcription, generation of HACCP training, automatic photo tagging, sales analytics", "resultsRu": "~30 внутренних сценариев применения; один сценарий (анализ схем ТО оборудования) прямо признан незрелым и свёрнут.", "resultsEn": "~30 internal use cases; one of them (analysis of equipment maintenance diagrams) was explicitly acknowledged as immature and discontinued.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "A2", "sectionRu": "A2. Франция", "sources": [ { "name": "Réussir Vigne", "url": "https://www.reussir.fr/vigne/filiere-vitivinicole-ils-gagnent-du-temps-grace-lintelligence-artificielle" } ] }, { "id": 47, "catalogId": 49, "slug": "satelai-gmv-47", "url": "https://vinumexmachina.com/casebook/cases/#case-47", "nameRu": "SATELAI (GMV)", "nameEn": "SATELAI (GMV)", "operatorRu": "Pago de Carraovejas (Рибера-дель-Дуэро)", "operatorEn": "Pago de Carraovejas (Ribera del Duero)", "countryRu": "Испания", "countryEn": "Spain", "domain": "viticulture", "tech": "yield", "stage": "commercial", "country": [ "es" ], "confidence": "a", "aiKind": "yes", "techRu": "Sentinel-2 + ML по 6 годам данных и 6 метеостанциям", "techEn": "Sentinel-2 + ML on 6 years of data and 6 weather stations", "doesRu": "Прогноз урожая за два месяца до сбора", "doesEn": "Yield forecast two months before harvest", "resultsRu": "Точность 92% в кампании 2022 и 97% в 2023 после добавления климатических параметров", "resultsEn": "92% accuracy in the 2022 campaign and 97% in 2023 after climate parameters were added", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2024, "yearDisplay": "2022–2024", "yearRaw": "2022–2024", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Pago de Carraovejas", "url": "https://www.pagodecarraovejas.com/viticultura-rendimiento-uva-satelite/" } ] }, { "id": 48, "catalogId": 50, "slug": "intelwines-48", "url": "https://vinumexmachina.com/casebook/cases/#case-48", "nameRu": "IntelWINES", "nameEn": "IntelWINES", "operatorRu": "Pago de Carraovejas + Университет Саламанки", "operatorEn": "Pago de Carraovejas + University of Salamanca", "countryRu": "Испания", "countryEn": "Spain", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "es" ], "confidence": "b", "aiKind": "yes", "techRu": "Сенсорные сети + тепловая съёмка с дрона 14 см/пиксель", "techEn": "Sensor networks + drone thermal imaging at 14 cm/pixel", "doesRu": "Прогноз потребности в поливе, снижение использования сульфитов", "doesEn": "Forecast of irrigation demand, reduction of sulphite use", "resultsRu": "Пилот 2019–2021, результаты не опубликованы.", "resultsEn": "Pilot 2019-2021, results not published.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2021, "yearDisplay": "2019–2021", "yearRaw": "2019–2021", "sectionKey": "A3", "sectionRu": "A3. 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Италия, Испания, Португалия", "sources": [ { "name": "CORDIS", "url": "https://cordis.europa.eu/project/id/869565" } ] }, { "id": 50, "catalogId": 52, "slug": "vinescout-horizon-2020-50", "url": "https://vinumexmachina.com/casebook/cases/#case-50", "nameRu": "VineScout (Horizon 2020)", "nameEn": "VineScout (Horizon 2020)", "operatorRu": "Symington Family Estates (Дору) и другие", "operatorEn": "Symington Family Estates (Douro) and others", "countryRu": "Испания, Португалия", "countryEn": "Spain, Portugal", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "es", "pt" ], "confidence": "a", "aiKind": "yes", "techRu": "Наземный робот с гиперспектральной камерой", "techEn": "Ground robot with a hyperspectral camera", "doesRu": "Мониторинг вигора и водного статуса лозы", "doesEn": "Monitoring of vine vigour and water status", "resultsRu": "€2,13 млн бюджета, €1,74 млн от ЕС; проектная цель — 5% рынка на 54 540 га европейских виноградников", "resultsEn": "€2.13m budget, €1.74m from the EU; the project's target is 5% of the market across 54,540 ha of European vineyards", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2020, "yearDisplay": "2016–2020", "yearRaw": "2016–2020", "sectionKey": "A3", "sectionRu": "A3. 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Итоговый отчёт самого проекта, опубликованный Еврокомиссией в CORDIS: оценки урожая на погонный метр показали «слабое или отсутствующее согласие и очень высокую ошибку»; даже при усреднении по 5–10 м оценки объясняли малую долю вариабельности и по-прежнему завышали урожай.", "resultsEn": "112 sessions, 27 plots, 17 grape varieties. The project's own final report, published by the European Commission on CORDIS: yield estimates per linear metre showed \"a low or absent agreement and a very high error\"; even averaged over 5–10 m, the estimates explained little of the variability and still overestimated the yield.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2013, "yearEnd": 2016, "yearDisplay": "2013–2016", "yearRaw": "2013–2016", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "CORDIS", "url": "https://cordis.europa.eu/project/id/605630/reporting" } ] }, { "id": 52, "catalogId": 54, "slug": "canopies-horizon-2020-52", "url": "https://vinumexmachina.com/casebook/cases/#case-52", "nameRu": "CANOPIES (Horizon 2020)", "nameEn": "CANOPIES (Horizon 2020)", "operatorRu": "Консорциум из 10 партнёров", "operatorEn": "A consortium of 10 partners", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "it" ], "confidence": "a", "aiKind": "yes", "techRu": "Двурукий мобильный манипулятор + ИИ-восприятие", "techEn": "Dual-arm mobile manipulator + AI perception", "doesRu": "Совместная с человеком уборка и обрезка столового винограда", "doesEn": "Human-collaborative harvesting and pruning of table grapes", "resultsRu": "€6,9 млн, 100% финансирование ЕС; 10 партнёров", "resultsEn": "€6.9m, 100% EU funding; 10 partners", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2024, "yearDisplay": "2021–2024", "yearRaw": "2021–2024", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "CORDIS", "url": "https://cordis.europa.eu/project/id/101016906" } ] }, { "id": 53, "catalogId": 55, "slug": "vinum-53", "url": "https://vinumexmachina.com/casebook/cases/#case-53", "nameRu": "VINUM", "nameEn": "VINUM", "operatorRu": "Пилот, Пьяченца", "operatorEn": "Pilot, Piacenza", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "Четвероногий робот + RGB-D зрение", "techEn": "Quadruped robot + RGB-D vision", "doesRu": "Автономная обрезка с выбором точки реза", "doesEn": "Autonomous pruning with selection of the cut point", "resultsRu": "Количественного сравнения с ручной обрезкой пока нет.", "resultsEn": "There is as yet no quantitative comparison with manual pruning.", "caveatRu": "Год начала 2018 цитируемым источником не подтверждается.", "caveatEn": "The 2018 start year is not confirmed by the cited source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2023, "yearDisplay": "2018–2023", "yearRaw": "2018–2023", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Informatore Agrario", "url": "https://www.informatoreagrario.it/meccanica/vinum-robot-quadrupede-per-la-potatura-in-vigneto/" } ] }, { "id": 54, "catalogId": 56, "slug": "villa-sandi-intelligent-vineyard-ecosystem-54", "url": "https://vinumexmachina.com/casebook/cases/#case-54", "nameRu": "Villa Sandi Intelligent Vineyard Ecosystem", "nameEn": "Villa Sandi Intelligent Vineyard Ecosystem", "operatorRu": "Villa Sandi (Венето, Фриули)", "operatorEn": "Villa Sandi (Veneto, Friuli)", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "IoT-датчики + дроны + спутник + ИИ-поддержка решений", "techEn": "IoT sensors + drones + satellite + AI decision support", "doesRu": "Интегрированный мониторинг участков", "doesEn": "Integrated monitoring of plots", "resultsRu": "200+ га подключено; обработки сокращены до 20%; вода — в среднем на 10%, на опытных делянках до 70%.", "resultsEn": "200+ ha connected; treatments cut by up to 20%; water by an average of 10%, and by up to 70% on trial plots.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2026, "yearDisplay": "2024–2026", "yearRaw": "2024–2026", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "PR Newswire", "url": "https://www.prnewswire.com/news-releases/villa-sandi-turns-its-vineyards-into-an-intelligent-ecosystem-for-precision-viticulture-302829846.html" } ] }, { "id": 55, "catalogId": 57, "slug": "sguardo-55", "url": "https://vinumexmachina.com/casebook/cases/#case-55", "nameRu": "SGUARDO", "nameEn": "SGUARDO", "operatorRu": "Consorzio Tutela Prosecco DOC, Университет Падуи, регион Венето", "operatorEn": "Consorzio Tutela Prosecco DOC, University of Padua, Veneto region", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "disease-weather", "stage": "research", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "Спутниковое считывание градиента хлорофилла + метеорадар", "techEn": "Satellite reading of the chlorophyll gradient + weather radar", "doesRu": "Мониторинг экстремальных погодных событий на всей территории DOC", "doesEn": "Monitoring of extreme weather events across the whole DOC territory", "resultsRu": "Проект одобрен, результатов пока нет.", "resultsEn": "The project has been approved; there are no results yet.", "caveatRu": "Источник от сентября 2024 сообщает лишь об одобрении проекта; полевые работы ещё не начаты.", "caveatEn": "The source, from September 2024, reports only the project's approval; field work has not yet begun.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Prosecco DOC", "url": "https://www.prosecco.wine/en/sguardo-satellite-monitoring-events/" } ] }, { "id": 56, "catalogId": 58, "slug": "elaisian-56", "url": "https://vinumexmachina.com/casebook/cases/#case-56", "nameRu": "Elaisian", "nameEn": "Elaisian", "operatorRu": "Famiglia Malvetani и другие хозяйства", "operatorEn": "Famiglia Malvetani and other estates", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "it" ], "confidence": "c", "aiKind": "yes", "techRu": "IoT-датчики + собственные ML-модели", "techEn": "IoT sensors + proprietary ML models", "doesRu": "Поддержка решений по поливу и защите", "doesEn": "Decision support for irrigation and crop protection", "resultsRu": "По платформе в целом (не только виноград): 50 000 га, 4 000 хозяйств, 20 стран, средняя экономия обработок 25%", "resultsEn": "For the platform as a whole (not only grapes): 50,000 ha, 4,000 estates, 20 countries, average saving on treatments of 25%", "caveatRu": "Цифры относятся ко всей платформе Elaisian по всем культурам, а не только к виноградникам.", "caveatEn": "The figures relate to the whole Elaisian platform across all crops, not only to vineyards.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Elaisian", "url": "https://www.elaisian.com/en/" } ] }, { "id": 57, "catalogId": 59, "slug": "evja-57", "url": "https://vinumexmachina.com/casebook/cases/#case-57", "nameRu": "Evja", "nameEn": "Evja", "operatorRu": "Хозяйства в 9 странах", "operatorEn": "Estates in 9 countries", "countryRu": "Весь мир", "countryEn": "International", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "Запатентованная сенсорная система + предиктивные агромодели", "techEn": "Patented sensor system + predictive agronomic models", "doesRu": "Полив, питание, защита растений", "doesEn": "Irrigation, nutrition, crop protection", "resultsRu": "4 патента; €4,2 млн pre-Series A в сентябре 2023 от CDP Venture Capital", "resultsEn": "4 patents; €4.2m pre-Series A in September 2023 from CDP Venture Capital", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "CDP Venture Capital", "url": "https://www.cdpventurecapital.it/en/news.page?contentId=COM32400" } ] }, { "id": 58, "catalogId": 60, "slug": "xfarm-technologies-xtrap-xidro-58", "url": "https://vinumexmachina.com/casebook/cases/#case-58", "nameRu": "xFarm Technologies (xTrap, xIdro)", "nameEn": "xFarm Technologies (xTrap, xIdro)", "operatorRu": "", "operatorEn": "", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "cv", "stage": "commercial", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "Распознавание изображений в ловушках + IoT-полив", "techEn": "Image recognition in traps + IoT irrigation", "doesRu": "Идентификация вредителей и автоматизация орошения", "doesEn": "Pest identification and irrigation automation", "resultsRu": "Премия Green Innovation на Enovitis in Campo 2024", "resultsEn": "Green Innovation award at Enovitis in Campo 2024", "caveatRu": "Цитируемый источник не называет ни одного хозяйства, использующего решение.", "caveatEn": "The cited source names no estate using the solution.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Gambero Rosso", "url": "https://www.gamberorosso.it/settimanale/notizie-trebicchieri/vincitori-innovation-challenge/" } ] }, { "id": 59, "catalogId": 61, "slug": "ivine-59", "url": "https://vinumexmachina.com/casebook/cases/#case-59", "nameRu": "iVine", "nameEn": "iVine", "operatorRu": "Fèlsina (Кьянти Классико), Mulini di Segalari (Больгери)", "operatorEn": "Fèlsina (Chianti Classico), Mulini di Segalari (Bolgheri)", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "it" ], "confidence": "c", "aiKind": "yes", "techRu": "Цифровой двойник полога по фото со смартфона + биометрический анализ", "techEn": "Digital twin of the canopy from smartphone photos + biometric analysis", "doesRu": "Дифференцированная обработка", "doesEn": "Differentiated treatment", "resultsRu": "Финансирование по программе PSR Тосканы; заявленная цель — до −50% средств защиты", "resultsEn": "Funding under Tuscany's PSR programme; the stated target is up to −50% of crop protection products", "caveatRu": "−50% средств защиты — заявленная цель проекта, а не измеренный результат.", "caveatEn": "−50% of crop protection products is the project's stated target, not a measured result.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2024, "yearDisplay": "2023–2024", "yearRaw": "2023–2024", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "AgroNotizie", "url": "https://agronotizie.imagelinenetwork.com/difesa-e-diserbo/2023/05/16/con-ivine-la-difesa-del-vigneto-e-sartoriale/79143" } ] }, { "id": 60, "catalogId": 62, "slug": "vigneto-sicuro-abruzzo-trace-technologies-60", "url": "https://vinumexmachina.com/casebook/cases/#case-60", "nameRu": "Vigneto Sicuro (Abruzzo Trace Technologies)", "nameEn": "Vigneto Sicuro (Abruzzo Trace Technologies)", "operatorRu": "Итальянские энологи", "operatorEn": "Italian oenologists", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "it" ], "confidence": "c", "aiKind": "yes", "techRu": "Алгоритм индекса риска по спутнику и метеоданным без полевых датчиков", "techEn": "Risk-index algorithm from satellite and weather data without field sensors", "doesRu": "Прогноз риска болезней и погодных событий", "doesEn": "Forecast of disease risk and weather events", "resultsRu": "По данным компании, точность 90–99% и 6 000+ зарегистрированных энологов", "resultsEn": "According to the company, 90-99% accuracy and 6,000+ registered oenologists", "caveatRu": "Обе цифры приводятся по заявлению компании и независимо не подтверждены.", "caveatEn": "Both figures are given on the company's own claim and are not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "AVV", "url": "https://avv.pt/a-inteligencia-artificial-entra-na-vinha-com-vigneto-sicuro-os-enologos-adaptam-se-as-mudancas-climaticas/" } ] }, { "id": 61, "catalogId": 63, "slug": "staffilo-61", "url": "https://vinumexmachina.com/casebook/cases/#case-61", "nameRu": "Staffilo", "nameEn": "Staffilo", "operatorRu": "Staffilo (органическое Просекко)", "operatorEn": "Staffilo (organic Prosecco)", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "it" ], "confidence": "c", "aiKind": "yes", "techRu": "Дроновый мониторинг + платформа Demetra", "techEn": "Drone monitoring + Demetra platform", "doesRu": "Контроль состояния растений", "doesEn": "Monitoring of plant condition", "resultsRu": "Сокращение расхода воды и пестицидов без раскрытия процентов", "resultsEn": "Reduction in water and pesticide use, with no percentages disclosed", "caveatRu": "Сокращение — заявление компании, независимой проверки нет.", "caveatEn": "The reduction is a company claim; there is no independent verification.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Rivista.ai", "url": "https://www.rivista.ai/2026/04/15/dal-vigneto-al-codice-come-lintelligenza-artificiale-sta-rivoluzionando-il-vino-italiano/" } ] }, { "id": 62, "catalogId": 64, "slug": "eyesontraps-62", "url": "https://vinumexmachina.com/casebook/cases/#case-62", "nameRu": "EyesOnTraps", "nameEn": "EyesOnTraps", "operatorRu": "Sogevinus Quintas, Adriano Ramos Pinto, Sogrape Vinhos (Дору)", "operatorEn": "Sogevinus Quintas, Adriano Ramos Pinto, Sogrape Vinhos (Douro)", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "pt" ], "confidence": "b", "aiKind": "yes", "techRu": "Компьютерное зрение + краудсенсинг в феромонных ловушках", "techEn": "Computer vision + crowdsensing in pheromone traps", "doesRu": "Профилактика вредителей", "doesEn": "Pest prevention", "resultsRu": "Ведёт Fraunhofer AICOS совместно с ADVID и GeoDouro.", "resultsEn": "Led by Fraunhofer AICOS together with ADVID and GeoDouro.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "Agroportal", "url": "https://www.agroportal.pt/eyesontraps-inteligencia-artificial-para-prevencao-de-pragas-nas-vinhas/" } ] }, { "id": 63, "catalogId": 65, "slug": "wine4cast-63", "url": "https://vinumexmachina.com/casebook/cases/#case-63", "nameRu": "Wine4cast", "nameEn": "Wine4cast", "operatorRu": "FCUP/INESC TEC + региональные производители и 6 малых предприятий", "operatorEn": "FCUP/INESC TEC + regional producers and 6 small enterprises", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "viticulture", "tech": "yield", "stage": "research", "country": [ "pt" ], "confidence": "a", "aiKind": "yes", "techRu": "Оптические и фотонные сенсоры, спутник, дрон, томография растений, ИИ", "techEn": "Optical and photonic sensors, satellite, drone, plant tomography, AI", "doesRu": "Национальная система прогноза продуктивности виноградников Португалии", "doesEn": "National system for forecasting the productivity of Portugal's vineyards", "resultsRu": "~€940 000, финансирование PRR; 3 года", "resultsEn": "~€940,000, PRR funding; 3 years", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2026, "yearDisplay": "2023–2026", "yearRaw": "2023–2026", "sectionKey": "A3", "sectionRu": "A3. Италия, Испания, Португалия", "sources": [ { "name": "U.Porto", "url": "https://noticias.up.pt/2023/01/20/projeto-da-u-porto-usa-inteligencia-artificial-para-prever-produtividade-das-vinhas/" } ] }, { "id": 64, "catalogId": 66, "slug": "agraria-64", "url": "https://vinumexmachina.com/casebook/cases/#case-64", "nameRu": "AgrarIA", "nameEn": "AgrarIA", "operatorRu": "Familia Torres (Пенедес)", "operatorEn": "Familia Torres (Penedès)", "countryRu": "Испания", "countryEn": "Spain", "domain": "viticulture", "tech": "yield", "stage": "pilot", "country": [ "es" ], "confidence": "a", "aiKind": "yes", "techRu": "Спутниковые снимки + агроклиматика + ИИ", "techEn": "Satellite imagery + agroclimatology + AI", "doesRu": "Прогнозирование сбора", "doesEn": "Harvest forecasting", "resultsRu": "Консорциум из 24 организаций под руководством GMV, часть Национальной стратегии ИИ Испании", "resultsEn": "A consortium of 24 organisations led by GMV, part of Spain's National AI Strategy", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2023, "yearDisplay": "2021–2023", "yearRaw": "2021–2023", "sectionKey": "A3", "sectionRu": "A3. 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Германия, Австрия, Швейцария", "sources": [ { "name": "Fraunhofer IOSB", "url": "https://www.iosb.fraunhofer.de/en/projects-and-products/digivine-digitalization-viticulture.html" } ] }, { "id": 71, "catalogId": 74, "slug": "phenoliner-jki-geilweilerhof-71", "url": "https://vinumexmachina.com/casebook/cases/#case-71", "nameRu": "Phenoliner (JKI Geilweilerhof)", "nameEn": "Phenoliner (JKI Geilweilerhof)", "operatorRu": "Институт селекции винограда JKI", "operatorEn": "JKI Institute for Grapevine Breeding", "countryRu": "Германия", "countryEn": "Germany", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "de" ], "confidence": "a", "aiKind": "yes", "techRu": "Мультисенсорная платформа: RGB, NIR, VNIR/SWIR", "techEn": "Multi-sensor platform: RGB, NIR, VNIR/SWIR", "doesRu": "Высокопроизводительное неразрушающее фенотипирование лозы", "doesEn": "High-throughput non-destructive phenotyping of the vine", "resultsRu": "RTK-GPS с точностью 2 см; RGB/NIR на 5 Гц, гиперспектр на 100–160 Гц", "resultsEn": "RTK-GPS accurate to 2 cm; RGB/NIR at 5 Hz, hyperspectral at 100–160 Hz", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2017, "yearDisplay": "2017", "yearRaw": "2017", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "Sensors", "url": "https://www.mdpi.com/1424-8220/17/7/1625" } ] }, { "id": 72, "catalogId": 75, "slug": "diwakopter-72", "url": "https://vinumexmachina.com/casebook/cases/#case-72", "nameRu": "DIWAKOPTER", "nameEn": "DIWAKOPTER", "operatorRu": "Hessische Staatsweingüter Kloster Eberbach (Рейнгау)", "operatorEn": "Hessische Staatsweingüter Kloster Eberbach (Rheingau)", "countryRu": "Германия", "countryEn": "Germany", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "de" ], "confidence": "b", "aiKind": "yes", "techRu": "Тракторный сенсор отражения листа + переменное дозирование", "techEn": "Tractor-mounted leaf reflectance sensor + variable-rate dosing", "doesRu": "Автоматическая корректировка дозы азота на каждую лозу", "doesEn": "Automatic adjustment of the nitrogen dose for each vine", "resultsRu": "€1,8 млн, 14 подпроектов; названо первым полевым испытанием метода в немецкоязычном виноградарстве.", "resultsEn": "€1.8m, 14 sub-projects; described as the first field trial of the method in German-speaking viticulture.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": null, "yearDisplay": "2022–", "yearRaw": "2022–", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "Wein.plus", "url": "https://magazine.wein.plus/news/geisenheim-university-of-applied-sciences-tests-sensor-controlled-precision-fertilisation-fertiliser-quantity-is-efficiently-adjusted-to-the-needs-of-the-individual-vine" } ] }, { "id": 73, "catalogId": 76, "slug": "smarter-weinberg-73", "url": "https://vinumexmachina.com/casebook/cases/#case-73", "nameRu": "Smarter Weinberg", "nameEn": "Smarter Weinberg", "operatorRu": "Виноградари Мозеля, Ара, Среднего Рейна", "operatorEn": "Winegrowers of the Mosel, the Ahr and the Mittelrhein", "countryRu": "Германия", "countryEn": "Germany", "domain": "viticulture", "tech": "robotics", "stage": "pilot", "country": [ "de" ], "confidence": "b", "aiKind": "yes", "techRu": "Частная сеть 5G + робот с распознаванием изображений + IoT", "techEn": "Private 5G network + robot with image recognition + IoT", "doesRu": "Автоматизация работ на крутых склонах", "doesEn": "Automation of work on steep slopes", "resultsRu": "Полоса восходящего канала более 100 МГц", "resultsEn": "Uplink bandwidth of more than 100 MHz", "caveatRu": "Полоса канала подтверждается сторонним изданием — на странице самого проекта её нет.", "caveatEn": "The bandwidth is confirmed by a third-party publication — it is not on the project's own page.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": null, "yearDisplay": "2021–", "yearRaw": "2021–", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "Smarter Weinberg", "url": "https://www.smarter-weinberg.de/" } ] }, { "id": 74, "catalogId": 77, "slug": "obrezka-s-ii-dlr-mosel-74", "url": "https://vinumexmachina.com/casebook/cases/#case-74", "nameRu": "Обрезка с ИИ (DLR Mosel)", "nameEn": "Pruning with AI (DLR Mosel)", "operatorRu": "DLR Mosel, Бернкастель-Кус", "operatorEn": "DLR Mosel, Bernkastel-Kues", "countryRu": "Германия", "countryEn": "Germany", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "de" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ + очки дополненной реальности", "techEn": "AI + augmented-reality glasses", "doesRu": "Обучение и подсказки по щадящему резу для профилактики болезней древесины", "doesEn": "Training and prompts on gentle pruning cuts to prevent wood diseases", "resultsRu": "Трёхлетний проект, количественных результатов не раскрыто.", "resultsEn": "A three-year project; no quantitative results disclosed.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2021, "yearDisplay": "2018–2021", "yearRaw": "2018–2021", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "DWM", "url": "https://www.dwm-aktuell.de/rebschnitt-kuenstlicher-intelligenz" } ] }, { "id": 75, "catalogId": 78, "slug": "smartvine-aqua4d-75", "url": "https://vinumexmachina.com/casebook/cases/#case-75", "nameRu": "SmartVine / Aqua4D", "nameEn": "SmartVine / Aqua4D", "operatorRu": "Виноградники коммуны Зальгеш (Вале, Швейцария)", "operatorEn": "Vineyards of the commune of Salgesch (Valais, Switzerland)", "countryRu": "Швейцария", "countryEn": "Switzerland", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "ch" ], "confidence": "b", "aiKind": "yes", "techRu": "Капельный полив + электромагнитная обработка воды + датчики влажности + дрон", "techEn": "Drip irrigation + electromagnetic water treatment + moisture sensors + drone", "doesRu": "Точное орошение в условиях альпийского дефицита воды", "doesEn": "Precision irrigation under Alpine water scarcity", "resultsRu": "−20% воды на опытной делянке при сопоставимом урожае и качестве; цель коммуны — более 40% экономии; тестовая площадка ~2 000 м²", "resultsEn": "−20% water on the trial plot with comparable yield and quality; the commune's target is more than 40% saving; test site ~2,000 m²", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2023, "yearDisplay": "2022–2023", "yearRaw": "2022–2023", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "SWI swissinfo", "url": "https://www.swissinfo.ch/ger/wissen-technik/schweizer-weindorf-erprobt-loesungen-gegen-wasserknappheit/48659922" } ] }, { "id": 76, "catalogId": 79, "slug": "weingartner-marbach-eg-76", "url": "https://vinumexmachina.com/casebook/cases/#case-76", "nameRu": "Weingärtner Marbach eG", "nameEn": "Weingärtner Marbach eG", "operatorRu": "Три семьи виноградарей, участок Alter Berg", "operatorEn": "Three winegrowing families, the Alter Berg site", "countryRu": "Германия", "countryEn": "Germany", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "de" ], "confidence": "b", "aiKind": "yes", "techRu": "LoRaWAN-датчики влажности почвы", "techEn": "LoRaWAN soil moisture sensors", "doesRu": "Решения по поливу в засуху", "doesEn": "Irrigation decisions in drought", "resultsRu": "6 датчиков в пилоте", "resultsEn": "6 sensors in the pilot", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "Rebe & Wein", "url": "https://www.rebeundwein.de/aktuelles/news/article-8252323-198999/smarte-sensoren-helfen-beim-effizienten-bewaessern-.html" } ] }, { "id": 77, "catalogId": 80, "slug": "agroscope-wadenswil-77", "url": "https://vinumexmachina.com/casebook/cases/#case-77", "nameRu": "Agroscope Wädenswil", "nameEn": "Agroscope Wädenswil", "operatorRu": "Швейцарские виноградники", "operatorEn": "Swiss vineyards", "countryRu": "Швейцария", "countryEn": "Switzerland", "domain": "viticulture", "tech": "remote-sensing", "stage": "research", "country": [ "ch" ], "confidence": "c", "aiKind": "yes", "techRu": "Автономная косилка + дрон для ранней детекции милдью", "techEn": "Autonomous mower + drone for early detection of downy mildew", "doesRu": "Прополка и доклиническая детекция болезни", "doesEn": "Weeding and pre-clinical detection of the disease", "resultsRu": "Результатов нет; директор скептичен относительно доступа дронов в плодовую зону на крутых швейцарских склонах.", "resultsEn": "No results; the director is sceptical about drone access to the fruiting zone on steep Swiss slopes.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "NZZ", "url": "https://www.nzz.ch/zuerich/der-roboter-im-rebberg-wie-technologie-den-weinanbau-veraendern-soll-ld.1415412" } ] }, { "id": 78, "catalogId": 81, "slug": "xarvio-field-manager-for-grapes-basf-78", "url": "https://vinumexmachina.com/casebook/cases/#case-78", "nameRu": "xarvio FIELD MANAGER for Grapes (BASF)", "nameEn": "xarvio FIELD MANAGER for Grapes (BASF)", "operatorRu": "Виноградари Франции, Испании, Турции", "operatorEn": "Winegrowers in France, Spain and Turkey", "countryRu": "Франция, Испания, Турция", "countryEn": "France, Spain, Türkiye", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "fr", "es", "tr" ], "confidence": "b", "aiKind": "yes", "techRu": "Агромодели (движок Hort@) для вредителей, болезней, полива, питания", "techEn": "Agronomic models (the Hort@ engine) for pests, diseases, irrigation and nutrition", "doesRu": "Рекомендации по обработкам на 100+ сортов винограда", "doesEn": "Treatment recommendations for 100+ grape varieties", "resultsRu": "Платформа xarvio в целом: 130 000+ пользователей, 20+ млн га; расходы BASF на НИОКР в цифровом земледелии — €919 млн в 2024", "resultsEn": "The xarvio platform as a whole: 130,000+ users, 20m+ ha; BASF's R&D spending on digital farming — €919m in 2024", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "ноябрь 2025", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "BASF", "url": "https://www.basf.com/global/de/media/news-releases/2025/11/p-25-227" } ] }, { "id": 79, "catalogId": 82, "slug": "boku-wien-79", "url": "https://vinumexmachina.com/casebook/cases/#case-79", "nameRu": "BOKU Wien", "nameEn": "BOKU Wien", "operatorRu": "Академические исследования", "operatorEn": "Academic research", "countryRu": "Австрия", "countryEn": "Austria", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "at" ], "confidence": "c", "aiKind": "yes", "techRu": "Геометрическое глубокое обучение на 3D-облаках точек", "techEn": "Geometric deep learning on 3D point clouds", "doesRu": "Анализ структуры лозы, фенотипирование", "doesEn": "Analysis of vine structure, phenotyping", "resultsRu": "Стадия конференционных докладов", "resultsEn": "At the stage of conference papers", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "A4", "sectionRu": "A4. Германия, Австрия, Швейцария", "sources": [ { "name": "Der Winzer", "url": "https://www.der-winzer.at/content/wein-und-obst/der-winzer/de/news/2023/01/digitalisierung-und-kuenstliche-intelligenz-im-weinbau.html" } ] }, { "id": 80, "catalogId": 84, "slug": "gaia-national-vineyard-scan-consilium-80", "url": "https://vinumexmachina.com/casebook/cases/#case-80", "nameRu": "GAIA / National Vineyard Scan (Consilium Technology + Wine Australia)", "nameEn": "GAIA / National Vineyard Scan (Consilium Technology + Wine Australia)", "operatorRu": "Национальная программа Австралии", "operatorEn": "Australian national programme", "countryRu": "Австралия", "countryEn": "Australia", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "au" ], "confidence": "a", "aiKind": "yes", "techRu": "ML по спутниковым снимкам Maxar", "techEn": "ML on Maxar satellite imagery", "doesRu": "Детекция и картирование каждого коммерческого виноградного блока страны", "doesEn": "Detection and mapping of every commercial vineyard block in the country", "resultsRu": "146 128 га, 75 961 блок, 463 718 км рядов; совпадение с ручной разметкой 95% по стране", "resultsEn": "146,128 ha, 75,961 blocks, 463,718 km of rows; 95% agreement with manual annotation nationwide", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2019, "yearDisplay": "2018–2019", "yearRaw": "2018–2019", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Wine Australia", "url": "https://www.wineaustralia.com/news/media-releases/first-ever-clear-picture-of-australias-vineyards" } ] }, { "id": 81, "catalogId": 85, "slug": "vitivisor-vitibox-universitet-adelaidy-aiml-81", "url": "https://vinumexmachina.com/casebook/cases/#case-81", "nameRu": "VitiVisor / VitiBox (Университет Аделаиды AIML)", "nameEn": "VitiVisor / VitiBox (University of Adelaide AIML)", "operatorRu": "Riverland Wine, Wine Australia, PIRSA", "operatorEn": "Riverland Wine, Wine Australia, PIRSA", "countryRu": "Австралия", "countryEn": "Australia", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "au" ], "confidence": "a", "aiKind": "yes", "techRu": "Глубокое обучение + мультисенсорный «чёрный ящик»", "techEn": "Deep learning + a multi-sensor “black box”", "doesRu": "Подсчёт почек и побегов, детекция соцветий, рекомендации по поливу и обрезке", "doesEn": "Counting buds and shoots, detecting inflorescences, recommendations on irrigation and pruning", "resultsRu": "Проект на $5 млн; точность детекции соцветий до 98%; конструкция открыта.", "resultsEn": "A $5m project; inflorescence detection accuracy up to 98%; the design is open.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2022, "yearDisplay": "2020–2022", "yearRaw": "2020–2022", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "University of Adelaide", "url": "https://www.adelaide.edu.au/aiml/news/term/vitivisor" } ] }, { "id": 82, "catalogId": 86, "slug": "cropsy-technologies-82", "url": "https://vinumexmachina.com/casebook/cases/#case-82", "nameRu": "Cropsy Technologies", "nameEn": "Cropsy Technologies", "operatorRu": "Коммерческие виноградарские хозяйства", "operatorEn": "Commercial grape-growing estates", "countryRu": "США, Франция, Новая Зеландия", "countryEn": "United States, France, New Zealand", "domain": "viticulture", "tech": "cv", "stage": "scaled", "country": [ "us", "fr", "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "Компьютерное зрение в реальном времени на тракторах и комбайнах", "techEn": "Real-time computer vision on tractors and harvesters", "doesRu": "Полозная аналитика болезней, качества обрезки, почек и урожая", "doesEn": "Per-vine analytics of disease, pruning quality, buds and yield", "resultsRu": "20 млн сканирований лоз за последние 12 месяцев; ~8 000 лоз в час; 40 активных сканеров", "resultsEn": "20m vine scans in the last 12 months; ~8,000 vines per hour; 40 active scanners", "caveatRu": "Названия хозяйств-заказчиков цитируемым источником не подтверждаются.", "caveatEn": "The names of the client estates are not confirmed by the cited source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2025, "yearDisplay": "2019–2025", "yearRaw": "2019–2025", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "University of Auckland", "url": "https://www.auckland.ac.nz/en/news/2025/05/13/agritech-start-up-cropsy-technologies-changing-viticulture.html" } ] }, { "id": 83, "catalogId": 87, "slug": "the-yield-sensing-83", "url": "https://vinumexmachina.com/casebook/cases/#case-83", "nameRu": "The Yield «Sensing+»", "nameEn": "The Yield “Sensing+”", "operatorRu": "Treasury Wine Estates, Penfolds Magill Estate", "operatorEn": "Treasury Wine Estates, Penfolds Magill Estate", "countryRu": "США, Австралия, Новая Зеландия", "countryEn": "United States, Australia, New Zealand", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "us", "au", "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "IoT-сеть + предиктивная микроклиматическая модель", "techEn": "IoT network + predictive microclimate model", "doesRu": "Прогнозы на 14 дней для обработок и сбора", "doesEn": "14-day forecasts for treatments and harvest", "resultsRu": "Двухлетний пилот перешёл в трёхлетний коммерческий контракт в 2020.", "resultsEn": "A two-year pilot became a three-year commercial contract in 2020.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2020, "yearDisplay": "2018–2020", "yearRaw": "2018–2020", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "itnews", "url": "https://www.itnews.com.au/news/treasury-wine-estates-predictive-ai-and-self-driving-vehicles-pay-off-600932" } ] }, { "id": 84, "catalogId": 88, "slug": "robotics-plus-prospr-yamaha-84", "url": "https://vinumexmachina.com/casebook/cases/#case-84", "nameRu": "Robotics Plus «Prospr» (→ Yamaha)", "nameEn": "Robotics Plus “Prospr” (→ Yamaha)", "operatorRu": "Treasury Wine Estates, виноградник Matua (Мальборо)", "operatorEn": "Treasury Wine Estates, Matua vineyard (Marlborough)", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "robotics", "stage": "ended", "country": [ "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономный модульный опрыскиватель", "techEn": "Autonomous modular sprayer", "doesRu": "Порядное опрыскивание, один оператор на несколько машин", "doesEn": "Row-by-row spraying, one operator to several machines", "resultsRu": "1,5 л/ч против 9–10 л/ч у дизельного трактора; в испытаниях на трёх виноградниках Мальборо расход топлива, по первым данным, снизился примерно на 70%; потенциал расширения до 150 га; компания куплена Yamaha Motor.", "resultsEn": "1.5 l/h against 9–10 l/h for a diesel tractor; early results from a trial across three Marlborough vineyards show fuel use down by around 70%; potential to expand to 150 ha; the company was bought by Yamaha Motor.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Rural News Group", "url": "https://www.ruralnewsgroup.co.nz/wine-grower/wg-machinery/vineyard-robots-marlborough-twe-robotics-plus-trial" } ] }, { "id": 85, "catalogId": 89, "slug": "smart-machine-oxin-85", "url": "https://vinumexmachina.com/casebook/cases/#case-85", "nameRu": "Smart Machine «Oxin»", "nameEn": "Smart Machine “Oxin”", "operatorRu": "Pernod Ricard Winemakers, виноградник Matapiro (Хокс-Бей)", "operatorEn": "Pernod Ricard Winemakers, Matapiro vineyard (Hawke's Bay)", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономная многофункциональная платформа", "techEn": "Autonomous multi-function platform", "doesRu": "Скашивание, мульчирование и дефолиация за один проход", "doesEn": "Mowing, mulching and defoliation in a single pass", "resultsRu": "2 машины на площадке; полное картирование блоков, настройка сети и обучение операторов заняли 2 недели.", "resultsEn": "2 machines on site; full block mapping, network setup and operator training took 2 weeks.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2024, "yearDisplay": "2023–2024", "yearRaw": "2023–2024", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Pernod Ricard Winemakers", "url": "https://www.pernod-ricard-winemakers.com/pernod-ricard-winemakers-revolutionary-oxin-robotic-tractor/" } ] }, { "id": 86, "catalogId": 90, "slug": "ucvision-occlusion-86", "url": "https://vinumexmachina.com/casebook/cases/#case-86", "nameRu": "UCVision «Occlusion»", "nameEn": "UCVision “Occlusion”", "operatorRu": "Университеты Кентербери и Линкольна; площадка, связанная с Cloudy Bay; Waipara Springs", "operatorEn": "The Universities of Canterbury and Lincoln; a site linked to Cloudy Bay; Waipara Springs", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "yield", "stage": "research", "country": [ "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "3D-реконструкция многокамерными роботами", "techEn": "3D reconstruction with multi-camera robots", "doesRu": "«Заглядывание» за листья для подсчёта гроздей", "doesEn": "“Looking” behind the leaves to count bunches", "resultsRu": "NZ$6 млн, 5 лет, финансирование MBIE; 3 000 лоз на 1,5 га — только вторичная площадка", "resultsEn": "NZ$6m, 5 years, MBIE funding; 3,000 vines on 1.5 ha — the secondary site only", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2025, "yearDisplay": "2020–2025", "yearRaw": "2020–2025", "sectionKey": "A5", "sectionRu": "A5. 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Австралия и Новая Зеландия", "sources": [ { "name": "Farmers Weekly", "url": "https://www.farmersweekly.co.nz/technology/scanning-robot-revolutionises-viticulture-counts/" } ] }, { "id": 88, "catalogId": 92, "slug": "vineye-88", "url": "https://vinumexmachina.com/casebook/cases/#case-88", "nameRu": "VinEye", "nameEn": "VinEye", "operatorRu": "Plant & Food Research, Integrape, Bitwise Agronomy; испытания в St Clair Family Estate", "operatorEn": "Plant & Food Research, Integrape, Bitwise Agronomy; trials at St Clair Family Estate", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "ML-классификация изображений на роботе Burro", "techEn": "ML image classification on a Burro robot", "doesRu": "Детекция вирусного лифролла в очном сравнении с обученным человеком", "doesEn": "Detection of leafroll virus in a head-to-head comparison with a trained human", "resultsRu": "60 га коммерческих испытаний в Хокс-Бей и Мальборо", "resultsEn": "60 ha of commercial trials in Hawke's Bay and Marlborough", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "RNZ", "url": "https://www.rnz.co.nz/news/country/512732/ai-takes-on-human-for-wine-disease-spotting-supremacy" } ] }, { "id": 89, "catalogId": 93, "slug": "maaratech-89", "url": "https://vinumexmachina.com/casebook/cases/#case-89", "nameRu": "MaaraTech", "nameEn": "MaaraTech", "operatorRu": "Университеты Окленда, Уаикато, Кентербери, Отаго; Plant & Food Research", "operatorEn": "The Universities of Auckland, Waikato, Canterbury and Otago; Plant & Food Research", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "nz" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ + робототехника, плюс социологическое исследование внедрения", "techEn": "AI + robotics, plus a sociological study of adoption", "doesRu": "Национальная программа роботизации садов и виноградников", "doesEn": "National programme for the robotisation of orchards and vineyards", "resultsRu": "5 лет, Endeavour Fund 2018", "resultsEn": "5 years, Endeavour Fund 2018", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2023, "yearDisplay": "2018–2023", "yearRaw": "2018–2023", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "University of Otago", "url": "https://www.otago.ac.nz/centre-sustainability/research/foodagriculture/maaratech-artificial-intelligence-in-orchards-and-vineyards" } ] }, { "id": 90, "catalogId": 94, "slug": "bragato-research-institute-90", "url": "https://vinumexmachina.com/casebook/cases/#case-90", "nameRu": "Bragato Research Institute", "nameEn": "Bragato Research Institute", "operatorRu": "Bragato / Университет Линкольна", "operatorEn": "Bragato / Lincoln University", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "nz" ], "confidence": "b", "aiKind": "yes", "techRu": "ML на данных о поведении опытных обрезчиков", "techEn": "ML on data about the behaviour of experienced pruners", "doesRu": "Формализация решений при обрезке лозы для автоматизации", "doesEn": "Formalising vine pruning decisions for automation", "resultsRu": "Программа по пино нуару, софинансируемая MBIE через Endeavour Programme: «применим машинное обучение для предсказания связи между химией вина и восприятием качества».", "resultsEn": "A Pinot Noir programme co-funded by MBIE through the Endeavour Programme: “we will apply machine learning to predict the relationship between wine chemistry and the perception of quality”.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Bragato — программа по пино нуару", "url": "https://bri.co.nz/portfolio/pinot-noir/" } ] }, { "id": 91, "catalogId": 95, "slug": "onside-intelligence-91", "url": "https://vinumexmachina.com/casebook/cases/#case-91", "nameRu": "Onside Intelligence", "nameEn": "Onside Intelligence", "operatorRu": "New Zealand Winegrowers (национальная программа биобезопасности)", "operatorEn": "New Zealand Winegrowers (national biosecurity programme)", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "viticulture", "tech": "other", "stage": "scaled", "country": [ "nz" ], "confidence": "a", "aiKind": "yes", "techRu": "Платформа прослеживаемости и сетевая аналитика перемещений", "techEn": "Traceability platform and network analytics of movements", "doesRu": "Ускорение реакции на биологические вторжения", "doesEn": "Faster response to biological incursions", "resultsRu": "600+ виноградарей и 700+ виноделен на платформе; планы биобезопасности станут обязательными для членов Sustainable Winegrowing NZ с 2026.", "resultsEn": "600+ growers and 700+ wineries on the platform; biosecurity plans will become mandatory for Sustainable Winegrowing NZ members from 2026.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Onside", "url": "https://www.getonside.com/customers/nz-winegrowers-case-study" } ] }, { "id": 92, "catalogId": 96, "slug": "ii-detektsiya-mramornogo-klopa-92", "url": "https://vinumexmachina.com/casebook/cases/#case-92", "nameRu": "ИИ-детекция мраморного клопа", "nameEn": "AI detection of the brown marmorated stink bug", "operatorRu": "Минсельхоз Австралии, CSIRO, Microsoft", "operatorEn": "Australian Department of Agriculture, CSIRO, Microsoft", "countryRu": "Австралия", "countryEn": "Australia", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "au" ], "confidence": "b", "aiKind": "yes", "techRu": "Мобильное распознавание изображений", "techEn": "Mobile image recognition", "doesRu": "Полевая идентификация карантинных вредителей, угрожающих виноградарству", "doesEn": "Field identification of quarantine pests threatening viticulture", "resultsRu": "Испытания с сезона BMSB 2022", "resultsEn": "Trials from the 2022 BMSB season", "caveatRu": "Источник описывает приложение как испытание, а не как работающую систему.", "caveatEn": "The source describes the application as a trial, not as a working system.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Winetitles", "url": "https://winetitles.com.au/artificial-intelligence-tool-trialled-for-high-risk-bug-detection/" } ] }, { "id": 93, "catalogId": 97, "slug": "avtonomnyy-park-twe-ssha-93", "url": "https://vinumexmachina.com/casebook/cases/#case-93", "nameRu": "Автономный парк TWE (США)", "nameEn": "TWE autonomous fleet (United States)", "operatorRu": "Treasury Wine Estates, американские виноградники", "operatorEn": "Treasury Wine Estates, vineyards in the United States", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Agtonomy, GUSS, Monarch, Robotics Plus, SwarmFarm, VitiBot, Yamaha", "techEn": "Agtonomy, GUSS, Monarch, Robotics Plus, SwarmFarm, VitiBot, Yamaha", "doesRu": "Мультивендорная автономная обработка", "doesEn": "Multi-vendor autonomous operations", "resultsRu": "325+ га обработано автономно в 2023 финансовом году.", "resultsEn": "325+ ha worked autonomously in the 2023 financial year.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "itnews", "url": "https://www.itnews.com.au/news/treasury-wine-estates-predictive-ai-and-self-driving-vehicles-pay-off-600932" } ] }, { "id": 94, "catalogId": 98, "slug": "complexica-larry-the-digital-analyst-94", "url": "https://vinumexmachina.com/casebook/cases/#case-94", "nameRu": "Complexica «Larry, the Digital Analyst»", "nameEn": "Complexica \"Larry, the Digital Analyst\"", "operatorRu": "Treasury Wine Estates", "operatorEn": "Treasury Wine Estates", "countryRu": "Австралия, Новая Зеландия", "countryEn": "Australia, New Zealand", "domain": "viticulture", "tech": "optimisation", "stage": "commercial", "country": [ "au", "nz" ], "confidence": "b", "aiKind": "yes", "techRu": "Прескриптивная аналитика", "techEn": "Prescriptive analytics", "doesRu": "Оптимизация торговых территорий, частоты визитов и логистики", "doesEn": "Optimisation of sales territories, visit frequency and logistics", "resultsRu": "TWE: 14 000+ га виноградников, 70+ брендов, 3 400+ сотрудников", "resultsEn": "TWE: 14,000+ ha of vineyards, 70+ brands, 3,400+ employees", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2018, "yearDisplay": "2018", "yearRaw": "2018", "sectionKey": "A5", "sectionRu": "A5. Австралия и Новая Зеландия", "sources": [ { "name": "Complexica", "url": "https://www.complexica.com/news/treasury-wine-estates-selects-complexicas-artificial-intelligence-software-to-optimise-sales-territories-and-resource-distribution" } ] }, { "id": 95, "catalogId": 99, "slug": "vendimia-5-0-inria-chile-corfo-95", "url": "https://vinumexmachina.com/casebook/cases/#case-95", "nameRu": "Vendimia 5.0 (Inria Chile + Corfo)", "nameEn": "Vendimia 5.0 (Inria Chile + Corfo)", "operatorRu": "Viña Concha y Toro", "operatorEn": "Viña Concha y Toro", "countryRu": "Чили", "countryEn": "Chile", "domain": "viticulture", "tech": "yield", "stage": "pilot", "country": [ "cl" ], "confidence": "a", "aiKind": "yes", "techRu": "Объяснимый ИИ (XAI)", "techEn": "Explainable AI (XAI)", "doesRu": "Прогноз объёма сбора, отслеживание фенологии, планирование приёмки винограда", "doesEn": "Harvest volume forecasting, phenology tracking, grape intake planning", "resultsRu": "1,5 млрд чилийских песо инвестиций (900 млн от Concha y Toro, 600 млн от Corfo), 5-летняя программа", "resultsEn": "1.5bn Chilean pesos of investment (900m from Concha y Toro, 600m from Corfo), a 5-year programme", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Inria Chile", "url": "https://inria.cl/en/inria-chile-and-vina-concha-y-toro-join-forces-lead-industrial-revolution-50" } ] }, { "id": 96, "catalogId": 100, "slug": "smart-agro-platform-96", "url": "https://vinumexmachina.com/casebook/cases/#case-96", "nameRu": "Smart Agro Platform", "nameEn": "Smart Agro Platform", "operatorRu": "Viña Concha y Toro", "operatorEn": "Viña Concha y Toro", "countryRu": "Чили", "countryEn": "Chile", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "cl" ], "confidence": "b", "aiKind": "yes", "techRu": "Точный полив по микрометеоданным и ML", "techEn": "Precision irrigation from micro-weather data and ML", "doesRu": "Планирование орошения", "doesEn": "Irrigation planning", "resultsRu": "Экономия 18% воды (~500 м³/га в год) на пилоте площадью 1 160 га", "resultsEn": "18% water saving (~500 m³/ha per year) on a 1,160 ha pilot", "caveatRu": "Масштабирование за пределы пилота источником не подтверждается.", "caveatEn": "Scaling beyond the pilot is not confirmed by the source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Diario Financiero", "url": "https://www.df.cl/df-lab/innovacion-y-startups/las-nuevas-lineas-de-trabajo-del-centro-de-investigacion-e-innovacion-de" } ] }, { "id": 97, "catalogId": 101, "slug": "centro-de-investigacion-e-innovacion-cii-97", "url": "https://vinumexmachina.com/casebook/cases/#case-97", "nameRu": "Centro de Investigación e Innovación (CII)", "nameEn": "Centro de Investigación e Innovación (CII)", "operatorRu": "Viña Concha y Toro", "operatorEn": "Viña Concha y Toro", "countryRu": "Чили", "countryEn": "Chile", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "cl" ], "confidence": "b", "aiKind": "yes", "techRu": "Big Data + ML в виноделии; «умные» ферментационные ёмкости", "techEn": "Big Data + ML in winemaking; \"smart\" fermentation tanks", "doesRu": "Управление ферментацией, ремонтажем, сроками сбора", "doesEn": "Management of fermentation, pump-overs and harvest timing", "resultsRu": "$6 млн на НИОКР за пять лет; отдельно $3,158 млн в 2025 году, рост на 14%", "resultsEn": "$6m on R&D over five years; separately $3.158m in 2025, up 14%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2025, "yearDisplay": "2017–2025", "yearRaw": "2017–2025", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Viña Concha y Toro", "url": "https://vinacyt.com/nuestros-pilares/innovacion/" } ] }, { "id": 98, "catalogId": 102, "slug": "wiseconn-dropcontrol-98", "url": "https://vinumexmachina.com/casebook/cases/#case-98", "nameRu": "WiseConn DropControl", "nameEn": "WiseConn DropControl", "operatorRu": "Виноградные регионы Чили, Калифорнии, Испании, Италии, Австралии", "operatorEn": "Grape-growing regions of Chile, California, Spain, Italy and Australia", "countryRu": "США, Италия, Австралия, Испания, Чили", "countryEn": "United States, Italy, Australia, Spain, Chile", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "us", "it", "au", "es", "cl" ], "confidence": "c", "aiKind": "yes", "techRu": "Облачная IoT-платформа с предиктивной аналитикой воды", "techEn": "Cloud IoT platform with predictive water analytics", "doesRu": "Автоматизация вентилей и фертигации", "doesEn": "Automation of valves and fertigation", "resultsRu": "По данным компании, 20 000 полевых узлов к 2024 (против 1 000 в 2017)", "resultsEn": "According to the company, 20,000 field nodes by 2024 (against 1,000 in 2017)", "caveatRu": "Цифра приводится по заявлению компании и независимо не подтверждена; привязка к годам взята из графики на сайте.", "caveatEn": "The figure comes from the company's own statement and is not independently confirmed; the attribution to years is taken from a graphic on the website.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2006, "yearEnd": 2024, "yearDisplay": "2006–2024", "yearRaw": "2006–2024", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "WiseConn", "url": "https://wiseconn.com/us/about-wiseconn/" } ] }, { "id": 99, "catalogId": 103, "slug": "kilimo-microsoft-99", "url": "https://vinumexmachina.com/casebook/cases/#case-99", "nameRu": "Kilimo + Microsoft", "nameEn": "Kilimo + Microsoft", "operatorRu": "Фермы долины Майпо (Чили)", "operatorEn": "Farms of the Maipo Valley (Chile)", "countryRu": "Чили", "countryEn": "Chile", "domain": "viticulture", "tech": "optimisation", "stage": "commercial", "country": [ "cl" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-планирование полива", "techEn": "AI irrigation planning", "doesRu": "Сокращение водопотребления", "doesEn": "Reducing water use", "resultsRu": "−13% воды на 450 га сельхозугодий, 1,5 млн м³ сэкономлено за 3 года; сельское хозяйство потребляет ~68% доступной воды в бассейне Майпо.", "resultsEn": "−13% water across 450 ha of farmland, 1.5m m³ saved over 3 years; agriculture consumes ~68% of the available water in the Maipo basin.", "caveatRu": "Цифры приводятся по данным Kilimo и относятся к сельхозугодьям в Майпо, а не именно к виноградникам: в репортаже Microsoft о работе Kilimo в Майпо названы сады миндаля, черешни, грецкого ореха и лимона, а виноград упоминается лишь у одной фермы, вступившей в программу капельного полива.", "caveatEn": "The figures are Kilimo's own and cover farmland in Maipo, not vineyards specifically: Microsoft's feature on Kilimo's work in Maipo names almond, cherry, walnut and lemon orchards, and mentions grapes at only one farm, which joined a drip-irrigation programme.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2025, "yearDisplay": "2022–2025", "yearRaw": "2022–2025", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Kilimo", "url": "https://kilimo.com/en/microsoft-and-kilimo-artificial-intelligence-for-smarter-irrigation-in-chile/" }, { "name": "Microsoft", "url": "https://news.microsoft.com/source/latam/features/ai/data-driven-farming-chile/?lang=en" } ] }, { "id": 100, "catalogId": 104, "slug": "taranis-ai2-100", "url": "https://vinumexmachina.com/casebook/cases/#case-100", "nameRu": "Taranis AI2", "nameEn": "Taranis AI2", "operatorRu": "100+ аргентинских хозяйств; Мендоса — существующая база, расширение планировалось в Сан-Хуан", "operatorEn": "100+ Argentine estates; Mendoza is the existing base, expansion into San Juan was planned", "countryRu": "Аргентина", "countryEn": "Argentina", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "ar" ], "confidence": "b", "aiKind": "yes", "techRu": "ML по аэроснимкам разрешением 0,5 мм", "techEn": "ML on aerial imagery at 0.5 mm resolution", "doesRu": "Детекция вредителей, болезней, дефицита питания за 48–72 часа", "doesEn": "Detection of pests, diseases and nutrient deficiency within 48–72 hours", "resultsRu": "300 000+ га облётано в сезоне 2017/18; $20 млн Series B.", "resultsEn": "300,000+ ha flown in the 2017/18 season; $20m Series B.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2018, "yearDisplay": "2018", "yearRaw": "2018", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Diario de Cuyo", "url": "https://www.diariodecuyo.com.ar/suplementos/Firma-israeli-aplica-inteligencia-artificial-en-vinedos-argentinos-20181116-0074.html" } ] }, { "id": 101, "catalogId": 105, "slug": "embrapa-crops-jahde-tecnologia-101", "url": "https://vinumexmachina.com/casebook/cases/#case-101", "nameRu": "Embrapa «Crops» + Jahde Tecnologia", "nameEn": "Embrapa \"Crops\" + Jahde Tecnologia", "operatorRu": "Кооператив Aurora, Vale dos Vinhedos (Бразилия)", "operatorEn": "Aurora cooperative, Vale dos Vinhedos (Brazil)", "countryRu": "Бразилия", "countryEn": "Brazil", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "br" ], "confidence": "a", "aiKind": "yes", "techRu": "Модель на данных метеостанций, доставка по SMS", "techEn": "Model on weather-station data, delivered by SMS", "doesRu": "Ежедневная утренняя рекомендация: нужна ли обработка от оидиума", "doesEn": "A daily morning recommendation: whether a powdery mildew treatment is needed", "resultsRu": "Валидировано в течение трёх лет на хозяйствах кооператива.", "resultsEn": "Validated over three years on the cooperative's estates.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "2021", "yearRaw": "2021", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Embrapa", "url": "https://www.embrapa.br/en/busca-de-noticias/-/noticia/66624026/embrapa-uva-e-vinho-lanca-ferramentas-para-viticultura-de-precisao-crops---sistema-de-monitoramento-de-doencas-e-aplicativo-uzum-uva" } ] }, { "id": 102, "catalogId": 106, "slug": "embrapa-uzum-uva-102", "url": "https://vinumexmachina.com/casebook/cases/#case-102", "nameRu": "Embrapa Uzum Uva", "nameEn": "Embrapa Uzum Uva", "operatorRu": "Виноградари Бразилии", "operatorEn": "Brazilian growers", "countryRu": "Бразилия", "countryEn": "Brazil", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "br" ], "confidence": "a", "aiKind": "yes", "techRu": "Диагностическое приложение с сопоставлением симптомов, работает офлайн", "techEn": "Diagnostic application with symptom matching, works offline", "doesRu": "Определение болезней, вредителей и физиологических нарушений", "doesEn": "Identification of diseases, pests and physiological disorders", "resultsRu": "Бесплатное приложение для Android", "resultsEn": "Free Android application", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "2021", "yearRaw": "2021", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Embrapa", "url": "https://www.embrapa.br/en/busca-de-noticias/-/noticia/66624026/embrapa-uva-e-vinho-lanca-ferramentas-para-viticultura-de-precisao-crops---sistema-de-monitoramento-de-doencas-e-aplicativo-uzum-uva" } ] }, { "id": 103, "catalogId": 107, "slug": "fruitlook-103", "url": "https://vinumexmachina.com/casebook/cases/#case-103", "nameRu": "FruitLook", "nameEn": "FruitLook", "operatorRu": "Виноградари и садоводы Западного Кейпа (ЮАР)", "operatorEn": "Grape growers and orchardists of the Western Cape (South Africa)", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "remote-sensing", "stage": "scaled", "country": [ "za" ], "confidence": "a", "aiKind": "yes", "techRu": "Спутниковое зондирование, алгоритм SEBAL", "techEn": "Satellite remote sensing, SEBAL algorithm", "doesRu": "Еженедельные данные по эвапотранспирации, росту и азотному статусу с разрешением 20×20 м", "doesEn": "Weekly data on evapotranspiration, growth and nitrogen status at 20×20 m resolution", "resultsRu": "Данные сезона 2014/15: 160 000+ га под еженедельным мониторингом; 8 287 поливных блоков / 15 608 га; виноград для вина — 23–24% блоков и площади; бюджет 3,5 млн рандов в год, для фермеров бесплатно", "resultsEn": "2014/15 season data: 160,000+ ha under weekly monitoring; 8,287 irrigation blocks / 15,608 ha; wine grapes are 23–24% of blocks and of area; budget 3.5m rand per year, free to farmers", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2011, "yearEnd": null, "yearDisplay": "2011–", "yearRaw": "2011–", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "GreenAgri", "url": "https://www.greenagri.org.za/assets/documents-/SmartAgri/Case-Studies/1.-Case-Study-FruitLook-FINAL.pdf" } ] }, { "id": 104, "catalogId": 108, "slug": "fruitlook-random-forest-104", "url": "https://vinumexmachina.com/casebook/cases/#case-104", "nameRu": "FruitLook + Random Forest", "nameEn": "FruitLook + Random Forest", "operatorRu": "Стелленбосский университет, Vinpro, Winetech", "operatorEn": "Stellenbosch University, Vinpro, Winetech", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "yield", "stage": "research", "country": [ "za" ], "confidence": "a", "aiKind": "yes", "techRu": "Random Forest по спутниковым переменным FruitLook", "techEn": "Random Forest on FruitLook satellite variables", "doesRu": "Модели оценки урожая по регионам и сортам", "doesEn": "Yield estimation models by region and grape variety", "resultsRu": "Общая точность 85% в регионе Олифантс-Ривер; лучшие результаты по шенен блан и коломбару; 5 сезонов данных", "resultsEn": "Overall accuracy 85% in the Olifants River region; best results for Chenin Blanc and Colombard; 5 seasons of data", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2019, "yearDisplay": "2018–2019", "yearRaw": "2018–2019", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Winetech Technical Yearbook 2019", "url": "https://user-hpa96tt.cld.bz/WINETECH-Technical-Yearbook-2019" } ] }, { "id": 105, "catalogId": 109, "slug": "sagwri-stellenbos-105", "url": "https://vinumexmachina.com/casebook/cases/#case-105", "nameRu": "SAGWRI (Стелленбос)", "nameEn": "SAGWRI (Stellenbosch)", "operatorRu": "Винная отрасль ЮАР", "operatorEn": "South African wine industry", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "yield", "stage": "research", "country": [ "za" ], "confidence": "a", "aiKind": "yes", "techRu": "ИИ-модели урожая и фенологии", "techEn": "AI yield and phenology models", "doesRu": "Подготовка методологической базы для отраслевых моделей", "doesEn": "Preparing the methodological basis for industry models", "resultsRu": "Проект стартовал в 2025, результатов нет.", "resultsEn": "The project started in 2025; there are no results.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Winetech", "url": "https://user-hpa96tt.cld.bz/South-Africa-Wine-Research-Projects-2025" } ] }, { "id": 106, "catalogId": 110, "slug": "kartirovanie-evapotranspiratsii-lozy-10-m-106", "url": "https://vinumexmachina.com/casebook/cases/#case-106", "nameRu": "Картирование эвапотранспирации лозы 10 м", "nameEn": "Vine evapotranspiration mapping at 10 m", "operatorRu": "Стелленбосский университет", "operatorEn": "Stellenbosch University", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "remote-sensing", "stage": "research", "country": [ "za" ], "confidence": "a", "aiKind": "yes", "techRu": "Спутник + вегетационные индексы", "techEn": "Satellite + vegetation indices", "doesRu": "Ежедневные карты водопотребления с разрешением 10 м", "doesEn": "Daily water-use maps at 10 m resolution", "resultsRu": "Начат в 2024.", "resultsEn": "Started in 2024.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Winetech", "url": "https://user-hpa96tt.cld.bz/South-Africa-Wine-Research-Projects-2025" } ] }, { "id": 107, "catalogId": 111, "slug": "portativnaya-ik-spektroskopiya-107", "url": "https://vinumexmachina.com/casebook/cases/#case-107", "nameRu": "Портативная ИК-спектроскопия", "nameEn": "Portable IR spectroscopy", "operatorRu": "Стелленбосский университет", "operatorEn": "Stellenbosch University", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "chemometrics", "stage": "research", "country": [ "za" ], "confidence": "a", "aiKind": "yes", "techRu": "Спектроскопия + хемометрическая калибровка", "techEn": "Spectroscopy + chemometric calibration", "doesRu": "Полевое определение углеводов, азота и аминокислот в органах лозы", "doesEn": "Field determination of carbohydrates, nitrogen and amino acids in vine organs", "resultsRu": "Начат в 2024.", "resultsEn": "Started in 2024.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Winetech", "url": "https://user-hpa96tt.cld.bz/South-Africa-Wine-Research-Projects-2025" } ] }, { "id": 108, "catalogId": 112, "slug": "terraclim-108", "url": "https://vinumexmachina.com/casebook/cases/#case-108", "nameRu": "TerraClim", "nameEn": "TerraClim", "operatorRu": "Винная отрасль ЮАР", "operatorEn": "South African wine industry", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "za" ], "confidence": "a", "aiKind": "yes", "techRu": "Платформа рельефных и климатических данных высокого разрешения", "techEn": "High-resolution terrain and climate data platform", "doesRu": "Подбор сортов и климатические решения", "doesEn": "Grape variety selection and climate decisions", "resultsRu": "Софинансирование Министерства науки и инноваций ЮАР", "resultsEn": "Co-funding from the South African Department of Science and Innovation", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "Winetech", "url": "https://user-hpa96tt.cld.bz/South-Africa-Wine-Research-Projects-2025" } ] }, { "id": 109, "catalogId": 113, "slug": "the-dassie-robot-x-109", "url": "https://vinumexmachina.com/casebook/cases/#case-109", "nameRu": "«The Dassie» (Robot X)", "nameEn": "\"The Dassie\" (Robot X)", "operatorRu": "Стелленбосский университет + CSIR", "operatorEn": "Stellenbosch University + CSIR", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "za" ], "confidence": "b", "aiKind": "yes", "techRu": "LiDAR, HD-камеры, датчики электромагнитной индукции почвы", "techEn": "LiDAR, HD cameras, soil electromagnetic induction sensors", "doesRu": "Автоматический сбор пространственных данных", "doesEn": "Automatic collection of spatial data", "resultsRu": "Прототип запущен в июне 2016, 12-месячная фаза испытаний.", "resultsEn": "Prototype launched in June 2016, a 12-month trial phase.", "caveatRu": "Сведений о продолжении проекта после испытаний нет.", "caveatEn": "There is no information on the project continuing after the trials.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2016, "yearDisplay": "2016", "yearRaw": "2016", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "IGWS", "url": "http://igws.co.za/article/in-the-news/press-releases/igws-launches-a-robotics-flagship-project" } ] }, { "id": 110, "catalogId": 114, "slug": "aerobotics-110", "url": "https://vinumexmachina.com/casebook/cases/#case-110", "nameRu": "Aerobotics", "nameEn": "Aerobotics", "operatorRu": "18 стран; столовый виноград, не винный", "operatorEn": "18 countries; table grapes, not wine grapes", "countryRu": "США, ЮАР", "countryEn": "United States, South Africa", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "us", "za" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-анализ снимков с дронов и спутников", "techEn": "AI analysis of drone and satellite imagery", "doesRu": "Здоровье деревьев, прогноз урожая", "doesEn": "Tree health, yield forecasting", "resultsRu": "$17 млн Series B в 2021; 81 млн+ деревьев обработано — показатели всей компании, преимущественно по цитрусовым.", "resultsEn": "$17m Series B in 2021; 81m+ trees processed — company-wide figures, mostly citrus.", "caveatRu": "Цифры относятся ко всей компании, в основном к цитрусовым; разделение на столовый и винный виноград источником не подтверждается.", "caveatEn": "The figures cover the whole company, mostly citrus; the split between table and wine grapes is not confirmed by the source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2014, "yearEnd": 2021, "yearDisplay": "2014–2021", "yearRaw": "2014–2021", "sectionKey": "A6", "sectionRu": "A6. Южная Америка и ЮАР", "sources": [ { "name": "TechCrunch", "url": "https://techcrunch.com/2021/01/21/south-africa-startup-aerobotics-raises-17m-led-by-naspers-foundry/" } ] }, { "id": 111, "catalogId": 115, "slug": "wine-of-moldova-ai-vintage-111", "url": "https://vinumexmachina.com/casebook/cases/#case-111", "nameRu": "Wine of Moldova «AI Vintage»", "nameEn": "Wine of Moldova \"AI Vintage\"", "operatorRu": "Национальное бюро продвижения вина Молдовы", "operatorEn": "National wine promotion office of Moldova", "countryRu": "Молдова", "countryEn": "Moldova", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "md" ], "confidence": "c", "aiKind": "yes", "techRu": "Сеть IoT-датчиков + генеративный ИИ", "techEn": "IoT sensor network + generative AI", "doesRu": "Тайминг сбора и решения по ферментации; ИИ-персона винодела «Chelaris»; ИИ-этикетки", "doesEn": "Harvest timing and fermentation decisions; the AI winemaker persona \"Chelaris\"; AI labels", "resultsRu": "По данным Wine of Moldova, 14 метеостанций на 12 демонстрационных виноградниках, 19 параметров данных, 3 винных региона; выпущено 2 готовых вина (Rubrum Aeon, Elysium).", "resultsEn": "According to Wine of Moldova, 14 weather stations on 12 demonstration vineyards, 19 data parameters, 3 wine regions; 2 finished wines released (Rubrum Aeon, Elysium).", "caveatRu": "Данные — самоотчёт национального отраслевого агентства, независимо не подтверждённый.", "caveatEn": "The data are self-reported by the national industry agency and not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "Wine of Moldova", "url": "https://ai.wineofmoldova.com" } ] }, { "id": 112, "catalogId": 116, "slug": "dji-agras-v-rumynii-112", "url": "https://vinumexmachina.com/casebook/cases/#case-112", "nameRu": "DJI Agras в Румынии", "nameEn": "DJI Agras in Romania", "operatorRu": "Румынские виноградари", "operatorEn": "Romanian growers", "countryRu": "Румыния", "countryEn": "Romania", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "ro" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономные дроны-опрыскиватели", "techEn": "Autonomous spraying drones", "doesRu": "Точное опрыскивание на склонах", "doesEn": "Precision spraying on slopes", "resultsRu": "Расход химии на склонах сокращён вдвое; по миру — около 400 000 агродронов DJI к концу 2024, +33% за год и +90% с 2020.", "resultsEn": "Chemical use on slopes halved; worldwide, around 400,000 DJI agricultural drones by the end of 2024, +33% over the year and +90% since 2020.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/dji-report-charts-rapid-rise-in-global-adoption-of-ag-spray-drones" } ] }, { "id": 113, "catalogId": 117, "slug": "deep-planet-vinesignal-113", "url": "https://vinumexmachina.com/casebook/cases/#case-113", "nameRu": "Deep Planet «VineSignal»", "nameEn": "Deep Planet \"VineSignal\"", "operatorRu": "Château Pape Clément (Франция), Koonara Wines (Австралия)", "operatorEn": "Château Pape Clément (France), Koonara Wines (Australia)", "countryRu": "США, Франция, Италия, Австралия, Великобритания, Португалия, Новая Зеландия", "countryEn": "United States, France, Italy, Australia, Portugal, United Kingdom, New Zealand", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "us", "fr", "it", "au", "pt", "gb", "nz" ], "confidence": "b", "aiKind": "yes", "techRu": "Спутник + ИИ", "techEn": "Satellite + AI", "doesRu": "Решения по дефолиации, высоте обрезки, обработке почвы; картирование органического углерода почвы", "doesEn": "Decisions on defoliation, pruning height and soil cultivation; soil organic carbon mapping", "resultsRu": "Платформа мониторит более 80 000 га, более 200 пользователей; заявленная экономия €45 на тонну винограда и прирост качества €2–20 на бутылку. Метрики платформенные, к конкретным хозяйствам не привязаны.", "resultsEn": "The platform monitors more than 80,000 ha, more than 200 users; claimed savings of €45 per tonne of grapes and a quality gain of €2–20 per bottle. The metrics are platform-wide and are not tied to specific estates.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "Deep Planet", "url": "https://www.deepplanet.ai" }, { "name": "Porto Protocol", "url": "https://www.portoprotocol.com/solution/deep-planet-vinesignal-an-innovative-vineyard-decision-support-platform/" } ] }, { "id": 114, "catalogId": 118, "slug": "trapview-sloveniya-114", "url": "https://vinumexmachina.com/casebook/cases/#case-114", "nameRu": "Trapview (Словения)", "nameEn": "Trapview (Slovenia)", "operatorRu": "50+ стран, включая винные регионы", "operatorEn": "50+ countries, including wine regions", "countryRu": "Весь мир", "countryEn": "International", "domain": "viticulture", "tech": "cv", "stage": "scaled", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "УФ-ловушка с компьютерным зрением и верификацией человеком", "techEn": "UV trap with computer vision and human verification", "doesRu": "Автоматический мониторинг лёта вредителей", "doesEn": "Automatic monitoring of pest flight", "resultsRu": "30 млн+ верифицированных изображений, 60+ видов насекомых, результат проверяется человеком в течение 24 часов.", "resultsEn": "30m+ verified images, 60+ insect species, the result is checked by a human within 24 hours.", "caveatRu": "Цифры относятся ко всей платформе и всем культурам, а не только к виноградникам.", "caveatEn": "The figures cover the whole platform and all crops, not only vineyards.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "Trapview", "url": "https://trapview.com" } ] }, { "id": 115, "catalogId": 119, "slug": "fasal-indiya-115", "url": "https://vinumexmachina.com/casebook/cases/#case-115", "nameRu": "Fasal (Индия)", "nameEn": "Fasal (India)", "operatorRu": "Индийские виноградари", "operatorEn": "Indian growers", "countryRu": "Индия", "countryEn": "India", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "in" ], "confidence": "c", "aiKind": "yes", "techRu": "ИИ + IoT", "techEn": "AI + IoT", "doesRu": "Прогноз болезней, рекомендации по обработкам и поливу, удалённое управление фертигацией", "doesEn": "Disease forecasting, treatment and irrigation recommendations, remote fertigation control", "resultsRu": "По всей платформе: 52 млрд литров воды сэкономлено, 127 000 кг снижения расхода химии (не только виноград).", "resultsEn": "Across the platform: 52bn litres of water saved, a 127,000 kg reduction in chemical use (not only grapes).", "caveatRu": "Совокупные показатели платформы по восьми культурам, по данным самой компании.", "caveatEn": "Aggregate platform figures across eight crops, according to the company itself.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "A7", "sectionRu": "A7. 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Остальной мир и глобальные платформы", "sources": [ { "name": "Bluewhite", "url": "https://www.bluewhite.ai" } ] }, { "id": 117, "catalogId": 121, "slug": "ecorobotix-117", "url": "https://vinumexmachina.com/casebook/cases/#case-117", "nameRu": "Ecorobotix", "nameEn": "Ecorobotix", "operatorRu": "20+ стран, полевые культуры", "operatorEn": "20+ countries, field crops", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "cv", "stage": "commercial", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-распознавание растений, ультраточное опрыскивание", "techEn": "AI plant recognition, ultra-precise spraying", "doesRu": "Заявлено до 95% сокращения расхода химии", "doesEn": "Claimed up to 95% reduction in chemical use", "resultsRu": "$150 млн привлечено за Series C и D (2024–2025); виноградное применение не подтверждено.", "resultsEn": "$150m raised across Series C and D (2024–2025); use on grapes is not confirmed.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2025, "yearDisplay": "2023–2025", "yearRaw": "2023–2025", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/ecorobotix-doubles-down-on-ai-software-for-precision-spraying-after-150m-raise" } ] }, { "id": 118, "catalogId": 122, "slug": "solinftec-solix-118", "url": "https://vinumexmachina.com/casebook/cases/#case-118", "nameRu": "Solinftec Solix", "nameEn": "Solinftec Solix", "operatorRu": "США, Бразилия, Колумбия, Китай, Мексика", "operatorEn": "United States, Brazil, Colombia, China, Mexico", "countryRu": "США, Китай, Бразилия, Колумбия, Мексика", "countryEn": "United States, China, Brazil, Colombia, Mexico", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "us", "cn", "br", "co", "mx" ], "confidence": "b", "aiKind": "yes", "techRu": "Солнечный автономный робот-скаут с 10+ сенсорами", "techEn": "Solar-powered autonomous scouting robot with 10+ sensors", "doesRu": "Разведка поля на скорости 1 миля/ч, самозаправляющиеся опрыскиватели", "doesEn": "Field scouting at 1 mph, self-refilling sprayers", "resultsRu": "300+ роботов, 35 млн акров под мониторингом; $50 000 за машину плюс подписка; виноград не подтверждён.", "resultsEn": "300+ robots, 35m acres monitored; $50,000 per machine plus a subscription; grapes not confirmed.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/solinftecs-self-refilling-spray-robots-close-the-loop-on-247-autonomy-on-the-farm" } ] }, { "id": 119, "catalogId": 123, "slug": "burro-119", "url": "https://vinumexmachina.com/casebook/cases/#case-119", "nameRu": "Burro", "nameEn": "Burro", "operatorRu": "6 стран, включая столовый виноград", "operatorEn": "6 countries, including table grapes", "countryRu": "США, Австралия, Новая Зеландия, Япония", "countryEn": "United States, Australia, New Zealand, Japan", "domain": "viticulture", "tech": "robotics", "stage": "commercial", "country": [ "us", "au", "nz", "jp" ], "confidence": "a", "aiKind": "yes", "techRu": "Автономный логистический робот-помощник на уборке", "techEn": "Autonomous logistics robot assisting at harvest", "doesRu": "Перевозка урожая между рядом и точкой приёмки", "doesEn": "Carrying the harvest between the row and the collection point", "resultsRu": "$24 млн Series B; 300+ роботов, 300 000+ автономных часов, 40+ клиентов", "resultsEn": "$24m Series B; 300+ robots, 300,000+ autonomous hours, 40+ customers", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "AgFunderNews", "url": "https://agfundernews.com/with-a-fresh-24m-burro-grows-from-people-to-pallet-scale-with-autonomous-harvest-assist-robots" } ] }, { "id": 120, "catalogId": 124, "slug": "winegb-infrastruktura-dannykh-120", "url": "https://vinumexmachina.com/casebook/cases/#case-120", "nameRu": "WineGB (инфраструктура данных)", "nameEn": "WineGB (data infrastructure)", "operatorRu": "Отрасль Англии и Уэльса", "operatorEn": "The industry of England and Wales", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "viticulture", "tech": "other", "stage": "commercial", "country": [ "gb" ], "confidence": "a", "aiKind": "adjacent", "techRu": "Отраслевая база и интерактивная карта", "techEn": "Industry database and interactive map", "doesRu": "Учёт и планирование сектора", "doesEn": "Sector record-keeping and planning", "resultsRu": "1 158 виноградников и 260 виноделен; 16,5 млн бутылок в 2025; рост продаж британского вина на 200% за 2018–2024; членство покрывает ~70% площадей.", "resultsEn": "1,158 vineyards and 260 wineries; 16.5m bottles in 2025; 200% growth in British wine sales over 2018–2024; membership covers ~70% of the area.", "caveatRu": "", "caveatEn": "", "whyRu": "Отраслевая база и интерактивная карта. Инфраструктура данных, а не анализ.", "whyEn": "Industry database and interactive map. Data infrastructure, not analysis.", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "A7", "sectionRu": "A7. Остальной мир и глобальные платформы", "sources": [ { "name": "WineGB", "url": "https://www.winegb.co.uk" } ] }, { "id": 121, "catalogId": 125, "slug": "schartner-pouget-et-al-universitet-zhenevy-121", "url": "https://vinumexmachina.com/casebook/cases/#case-121", "nameRu": "Schartner, Pouget et al., Университет Женевы", "nameEn": "Schartner, Pouget et al., University of Geneva", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "Франция", "countryEn": "France", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Сырые хроматограммы ГХ + линейный дискриминантный анализ", "techEn": "Raw GC chromatograms + linear discriminant analysis", "doesRu": "Определяет хозяйство и винтаж напрямую из сырой хроматограммы, без идентификации пиков", "doesEn": "Identifies the estate and the vintage directly from the raw chromatogram, without peak identification", "resultsRu": "Точность определения хозяйства 99% (N = 80 вин, 7 хозяйств Бордо). По винтажу: до 50% на самых информативных участках хроматограммы и 27% на полной хроматограмме — при случайной базовой линии 8% (12 классов винтажей).", "resultsEn": "Estate identification accuracy 99% (N = 80 wines, 7 Bordeaux estates). For vintage: up to 50% on the most informative regions of the chromatogram and 27% on the full chromatogram — against a random baseline of 8% (12 vintage classes).", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Communications Chemistry", "url": "https://www.nature.com/articles/s42004-023-01051-9" } ] }, { "id": 122, "catalogId": 126, "slug": "gonzalez-viejo-fuentes-universitet-melburna-122", "url": "https://vinumexmachina.com/casebook/cases/#case-122", "nameRu": "Gonzalez Viejo & Fuentes, Университет Мельбурна", "nameEn": "Gonzalez Viejo & Fuentes, University of Melbourne", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "Австралия", "countryEn": "Australia", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "au" ], "confidence": "a", "aiKind": "yes", "techRu": "Дешёвый электронный нос на 9 сенсорах + NIR + нейросеть", "techEn": "Low-cost 9-sensor electronic nose + NIR + neural network", "doesRu": "Классификация 12 категорий винных пороков (бретт, ТСА, гваякол, ацетальдегид, летучая кислотность, меркаптаны)", "doesEn": "Classification of 12 categories of wine fault (brett, TCA, guaiacol, acetaldehyde, volatile acidity, mercaptans)", "resultsRu": "Точность 90–97% по электронному носу и 94–97% по NIR; ~396 образцов", "resultsEn": "Accuracy 90–97% for the electronic nose and 94–97% for NIR; ~396 samples", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Sensors", "url": "https://www.mdpi.com/1424-8220/22/6/2303" } ] }, { "id": 123, "catalogId": 127, "slug": "sarlo-et-al-universitet-lion-1-123", "url": "https://vinumexmachina.com/casebook/cases/#case-123", "nameRu": "Sarlo et al., Университет Лион 1", "nameEn": "Sarlo et al., University of Lyon 1", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "Франция", "countryEn": "France", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Минеральный профиль (ICP) + XGBoost", "techEn": "Mineral profile (ICP) + XGBoost", "doesRu": "Предсказывает страну, французский регион и сорт по минеральному «отпечатку»", "doesEn": "Predicts country, French region and grape variety from the mineral \"fingerprint\"", "resultsRu": "Страна 92%, французский регион 91%, сорт 85%; специфичность выше 99%; база из 12 966 профилей", "resultsEn": "Country 92%, French region 91%, grape variety 85%; specificity above 99%; a database of 12,966 profiles", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "OENO One", "url": "https://oeno-one.eu/article/view/8107" } ] }, { "id": 124, "catalogId": 128, "slug": "hategan-et-al-kluzh-napoka-124", "url": "https://vinumexmachina.com/casebook/cases/#case-124", "nameRu": "Hategan et al., Клуж-Напока", "nameEn": "Hategan et al., Cluj-Napoca", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "Румыния", "countryEn": "Romania", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "ro" ], "confidence": "a", "aiKind": "yes", "techRu": "ЯМР-спектроскопия + kNN и логистическая регрессия", "techEn": "NMR spectroscopy + kNN and logistic regression", "doesRu": "Классификация сорта, региона и винтажа белых вин", "doesEn": "Classification of grape variety, region and vintage of white wines", "resultsRu": "Выше 98% при кросс-валидации, до 100% на тесте; N = 65", "resultsEn": "Above 98% under cross-validation, up to 100% on the test set; N = 65", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Beverages", "url": "https://www.mdpi.com/2306-5710/11/2/45" } ] }, { "id": 125, "catalogId": 129, "slug": "ferrier-block-uc-davis-125", "url": "https://vinumexmachina.com/casebook/cases/#case-125", "nameRu": "Ferrier & Block, UC Davis", "nameEn": "Ferrier & Block, UC Davis", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "США", "countryEn": "United States", "domain": "winemaking", "tech": "optimisation", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Нейросеть, моделирующая нелинейный сенсорный отклик на пропорции купажа", "techEn": "Neural network modelling the non-linear sensory response to blend proportions", "doesRu": "Сокращает число пробных купажей, нужных для нахождения оптимума", "doesEn": "Reduces the number of trial blends needed to find the optimum", "resultsRu": "Менее 2% ошибки состава при 30% сокращении числа проб; до 11% ошибки при 50% сокращении", "resultsEn": "Under 2% composition error with a 30% reduction in the number of trials; up to 11% error with a 50% reduction", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2001, "yearEnd": 2001, "yearDisplay": "2001", "yearRaw": "2001", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "AJEV", "url": "https://www.ajevonline.org/content/52/4/386" } ] }, { "id": 126, "catalogId": 130, "slug": "tan-oberholster-tagkopoulos-et-al-uc-davis-126", "url": "https://vinumexmachina.com/casebook/cases/#case-126", "nameRu": "Tan, Oberholster, Tagkopoulos et al., UC Davis (институт ИИ USDA-NIFA)", "nameEn": "Tan, Oberholster, Tagkopoulos et al., UC Davis (USDA-NIFA AI institute)", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "США", "countryEn": "United States", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "Lasso-регрессия, SVR, Random Forest по профилю летучих соединений", "techEn": "Lasso regression, SVR, Random Forest on the volatile compound profile", "doesRu": "Прогноз сенсорного индекса дымового привкуса", "doesEn": "Prediction of the smoke taint sensory index", "resultsRu": "Сравнение четырёх семейств моделей (линейные, Lasso, SVM, Random Forest); код открыт.", "resultsEn": "A comparison of four model families (linear, Lasso, SVM, Random Forest); the code is open.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "JAFC", "url": "https://doi.org/10.1021/acs.jafc.3c07019" } ] }, { "id": 127, "catalogId": 131, "slug": "prognoz-smouk-teynta-po-nir-ann-127", "url": "https://vinumexmachina.com/casebook/cases/#case-127", "nameRu": "Прогноз смоук-тейнта по NIR + ANN", "nameEn": "Smoke taint prediction from NIR + ANN", "operatorRu": "Университет Мельбурна (AWRI — внешняя референс-лаборатория)", "operatorEn": "University of Melbourne (AWRI — external reference laboratory)", "countryRu": "Австралия", "countryEn": "Australia", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "au" ], "confidence": "a", "aiKind": "yes", "techRu": "NIR-спектроскопия + нейросеть", "techEn": "NIR spectroscopy + neural network", "doesRu": "Прогноз уровня летучих фенолов и гликоконъюгатов в ягодах, сусле и вине", "doesEn": "Prediction of the level of volatile phenols and glycoconjugates in berries, must and wine", "resultsRu": "R² = 0,95–0,99 по пяти моделям; 540 образцов ягод", "resultsEn": "R² = 0.95–0.99 across five models; 540 berry samples", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2020, "yearDisplay": "2020", "yearRaw": "2020", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "OENO One", "url": "https://oeno-one.eu/article/view/4501" } ] }, { "id": 128, "catalogId": 132, "slug": "model-sensornogo-profilya-pino-nuara-128", "url": "https://vinumexmachina.com/casebook/cases/#case-128", "nameRu": "Модель сенсорного профиля пино нуара", "nameEn": "Pinot noir sensory profile model", "operatorRu": "Бутиковое хозяйство, Macedon Ranges", "operatorEn": "Boutique estate, Macedon Ranges", "countryRu": "Австралия", "countryEn": "Australia", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "au" ], "confidence": "a", "aiKind": "yes", "techRu": "Нейросетевая регрессия", "techEn": "Neural network regression", "doesRu": "Прогноз 19 сенсорных дескрипторов и цвета вина по NIR, погоде и агроприёмам", "doesEn": "Prediction of 19 sensory descriptors and wine colour from NIR, weather and agronomic practices", "resultsRu": "R = 0,92 по NIR; R = 0,98 «погода → сенсорика»; R = 0,99 «погода → цвет»; 9 винтажей, панель из 12 человек", "resultsEn": "R = 0.92 from NIR; R = 0.98 \"weather → sensory\"; R = 0.99 \"weather → colour\"; 9 vintages, a panel of 12 people", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2020, "yearDisplay": "2020", "yearRaw": "2020", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Sensors", "url": "https://www.mdpi.com/1424-8220/20/13/3618" } ] }, { "id": 129, "catalogId": 133, "slug": "obzor-ot-profilya-letuchikh-k-sensorike-utad-129", "url": "https://vinumexmachina.com/casebook/cases/#case-129", "nameRu": "Обзор «от профиля летучих к сенсорике», UTAD", "nameEn": "Review \"from volatile profile to sensory\", UTAD", "operatorRu": "Рецензируемый обзор", "operatorEn": "Peer-reviewed review", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "pt" ], "confidence": "a", "aiKind": "yes", "techRu": "Сводка PLSR, SVR, глубоких сетей, LDA", "techEn": "Summary of PLSR, SVR, deep networks, LDA", "doesRu": "Агрегирует опубликованную точность моделей «химия → сенсорика»", "doesEn": "Aggregates published accuracy of \"chemistry → sensory\" models", "resultsRu": "SVR до R = 0,96 (коэффициент корреляции, не R²); глубокие сети R² выше 0,96; классификация LDA выше 97%; предел обнаружения ТСА электронным носом 1,4 нг/л — ниже человеческого порога", "resultsEn": "SVR up to R = 0.96 (correlation coefficient, not R²); deep networks R² above 0.96; LDA classification above 97%; TCA detection limit for the electronic nose 1.4 ng/l — below the human threshold", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Chemosensors", "url": "https://www.mdpi.com/2227-9040/13/9/337" } ] }, { "id": 130, "catalogId": 134, "slug": "obzor-izotopnogo-analiza-ml-130", "url": "https://vinumexmachina.com/casebook/cases/#case-130", "nameRu": "Обзор изотопного анализа + ML", "nameEn": "Review of isotope analysis + ML", "operatorRu": "Рецензируемый обзор", "operatorEn": "Peer-reviewed review", "countryRu": "Китай", "countryEn": "China", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "cn" ], "confidence": "a", "aiKind": "yes", "techRu": "δ13C, δ2H, δ18O, 87Sr/86Sr + нейросети, Random Forest, PLS-DA, SVM", "techEn": "δ13C, δ2H, δ18O, 87Sr/86Sr + neural networks, Random Forest, PLS-DA, SVM", "doesRu": "Прослеживание географического происхождения и выявление фальсификации", "doesEn": "Tracing geographical origin and detecting adulteration", "resultsRu": "64–91,2% — это диапазон одного исследования по крепким напиткам, а не свод по многим работам. Порог «не ниже 90% на уровне страны» — рекомендуемый обзором критерий адекватности, а не достигнутый результат.", "resultsEn": "64–91.2% is the range from a single study on spirits, not a summary across many works. The threshold of \"no less than 90% at country level\" is an adequacy criterion recommended by the review, not an achieved result.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Foods", "url": "https://www.mdpi.com/2304-8158/14/6/943" } ] }, { "id": 131, "catalogId": 135, "slug": "conesa-celdran-et-al-universitet-migelya-131", "url": "https://vinumexmachina.com/casebook/cases/#case-131", "nameRu": "Conesa Celdrán et al., Университет Мигеля Эрнандеса", "nameEn": "Conesa Celdrán et al., Miguel Hernández University", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "Испания", "countryEn": "Spain", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "es" ], "confidence": "b", "aiKind": "yes", "techRu": "8 газовых сенсоров на Arduino Nano + PCA и k-means", "techEn": "8 gas sensors on an Arduino Nano + PCA and k-means", "doesRu": "Различение сортов Риохи: грасиано, гарнача, темпранильо, масуэло", "doesEn": "Discrimination of Rioja grape varieties: graciano, garnacha, tempranillo, mazuelo", "resultsRu": "100% точность при кластеризации, но N = 21 анализ — выборка слишком мала для выводов.", "resultsEn": "100% accuracy in clustering, but N = 21 analyses — the sample is too small for conclusions.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Agronomy", "url": "https://www.mdpi.com/2073-4395/12/11/2627" } ] }, { "id": 132, "catalogId": 136, "slug": "vismara-et-al-lirmm-monpele-132", "url": "https://vinumexmachina.com/casebook/cases/#case-132", "nameRu": "Vismara et al., LIRMM Монпелье", "nameEn": "Vismara et al., LIRMM Montpellier", "operatorRu": "Рецензируемое исследование", "operatorEn": "Peer-reviewed study", "countryRu": "Франция", "countryEn": "France", "domain": "winemaking", "tech": "optimisation", "stage": "research", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Программирование в ограничениях, ветви и границы", "techEn": "Constraint programming, branch and bound", "doesRu": "Многокритериальная оптимизация состава купажа при энологических ограничениях", "doesEn": "Multi-criteria optimisation of blend composition under oenological constraints", "resultsRu": "Демонстрация масштабирования на реальных задачах", "resultsEn": "A demonstration of scaling on real problems", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2015, "yearEnd": 2015, "yearDisplay": "2015", "yearRaw": "2015", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Constraints", "url": "https://link.springer.com/article/10.1007/s10601-015-9235-5" } ] }, { "id": 133, "catalogId": 137, "slug": "obzor-precision-enology-universitet-kordovy-133", "url": "https://vinumexmachina.com/casebook/cases/#case-133", "nameRu": "Обзор «Precision Enology», Университет Кордовы", "nameEn": "Review \"Precision Enology\", University of Córdoba", "operatorRu": "Рецензируемый обзор", "operatorEn": "Peer-reviewed review", "countryRu": "Испания", "countryEn": "Spain", "domain": "winemaking", "tech": "sensors-iot", "stage": "research", "country": [ "es" ], "confidence": "a", "aiKind": "yes", "techRu": "Каталог коммерческих систем мониторинга ферментации", "techEn": "Catalogue of commercial fermentation monitoring systems", "doesRu": "Перечисляет доступное на рынке оборудование", "doesEn": "Lists the equipment available on the market", "resultsRu": "Названы Winegrid Wineplus 1110 (Португалия), Enartis B-evolution (Италия), Precision Fermentation BrewIQ, Anton Paar 5100 (Австрия).", "resultsEn": "Names Winegrid Wineplus 1110 (Portugal), Enartis B-evolution (Italy), Precision Fermentation BrewIQ, Anton Paar 5100 (Austria).", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Fermentation", "url": "https://www.mdpi.com/2311-5637/12/4/187" } ] }, { "id": 134, "catalogId": 138, "slug": "tastry-134", "url": "https://vinumexmachina.com/casebook/cases/#case-134", "nameRu": "Tastry", "nameEn": "Tastry", "operatorRu": "Малые и средние винодельни, ретейл; потребительский сервис BottleBird", "operatorEn": "Small and medium wineries, retail; the consumer service BottleBird", "countryRu": "США", "countryEn": "United States", "domain": "winemaking", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Лабораторный химанализ + ML-сопоставление с базой потребительских предпочтений", "techEn": "Laboratory chemical analysis + ML matching against a database of consumer preferences", "doesRu": "Соотносит химический профиль вина с индивидуальным вкусом покупателя", "doesEn": "Matches a wine's chemical profile to an individual buyer's taste", "resultsRu": "Компания заявляет точность выше 92% и рост валовых продаж у ретейлеров до 20%.", "resultsEn": "The company claims accuracy above 92% and growth in gross sales at retailers of up to 20%.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2024, "yearDisplay": "2016–2024", "yearRaw": "2016–2024", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Forbes", "url": "https://www.forbes.com/sites/bernardmarr/2021/06/28/artificial-intelligence-can-now-tastetransforming-winemaking-with-tastry/" } ] }, { "id": 135, "catalogId": 139, "slug": "enologix-135", "url": "https://vinumexmachina.com/casebook/cases/#case-135", "nameRu": "Enologix", "nameEn": "Enologix", "operatorRu": "Beaulieu Vineyard, Cakebread Cellars, Ridge Vineyards, Joseph Phelps, Peter Michael, Diamond Creek", "operatorEn": "Beaulieu Vineyard, Cakebread Cellars, Ridge Vineyards, Joseph Phelps, Peter Michael, Diamond Creek", "countryRu": "США", "countryEn": "United States", "domain": "winemaking", "tech": "chemometrics", "stage": "unconfirmed", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Корреляция «химия → оценка критика» по фенольным и терпеновым профилям", "techEn": "Correlation of \"chemistry → critic score\" from phenolic and terpene profiles", "doesRu": "Прогноз оптимальной даты сбора, оценки критика и состава купажа", "doesEn": "Prediction of the optimal harvest date, the critic score and blend composition", "resultsRu": "Методология оспаривалась академическим сообществом, включая Роджера Болтона из UC Davis. По заявлению компании, попадание в оценку критика с точностью до 2,5 балла в 95% случаев; база из 50 000+ вин к 2005 году.", "resultsEn": "The methodology was contested by the academic community, including Roger Boulton of UC Davis. According to the company, the critic score is matched to within 2.5 points in 95% of cases; a database of 50,000+ wines by 2005.", "caveatRu": "Цифры приводятся по заявлению компании.", "caveatEn": "The figures are given according to the company.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 1989, "yearEnd": 2006, "yearDisplay": "1989–2006", "yearRaw": "1989–2006", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Wikipedia / press", "url": "https://en.wikipedia.org/wiki/Enologix" } ] }, { "id": 136, "catalogId": 140, "slug": "bruker-nmr-wine-profiling-4-0-136", "url": "https://vinumexmachina.com/casebook/cases/#case-136", "nameRu": "Bruker NMR Wine-Profiling 4.0", "nameEn": "Bruker NMR Wine-Profiling 4.0", "operatorRu": "Сертификационные лаборатории", "operatorEn": "Certification laboratories", "countryRu": "Испания", "countryEn": "Spain", "domain": "winemaking", "tech": "chemometrics", "stage": "scaled", "country": [ "es" ], "confidence": "a", "aiKind": "yes", "techRu": "Количественная ЯМР-спектроскопия + фингерпринтинг против референсной базы", "techEn": "Quantitative NMR spectroscopy + fingerprinting against a reference database", "doesRu": "Количественный анализ состава вина за одно измерение; выявление фальсификации и неверной маркировки", "doesEn": "Quantitative analysis of wine composition in a single measurement; detection of adulteration and mislabelling", "resultsRu": "ЯМР-спектроскопия включена в Компендиум международных методов анализа вин и сусел OIV в 2021 году как метод количественного определения шести показателей вина: глюкозы, яблочной, уксусной, фумаровой, шикимовой и сорбиновой кислот.", "resultsEn": "NMR spectroscopy was included in the OIV Compendium of International Methods of Analysis of Wines and Musts in 2021 as a method for quantifying six wine parameters: glucose and malic, acetic, fumaric, shikimic and sorbic acids.", "caveatRu": "Выявление фальсификации и неверной маркировки — назначение, которое своему модулю Wine-Profiling 4.0 приписывает сама Bruker; в методе, принятом OIV (резолюция OIV-OENO 618-2020), о фальсификации и подлинности не говорится.", "caveatEn": "Detecting adulteration and mislabelling is the use Bruker itself claims for its Wine-Profiling 4.0 module; the method the OIV adopted (resolution OIV-OENO 618-2020) says nothing about adulteration or authenticity.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2021, "yearDisplay": "2020–2021", "yearRaw": "2020–2021", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Bruker — включение в Компендиум OIV, 2021", "url": "https://www.bruker.com/en/news-and-events/news/2021/international-organization-of-vine-and-wine-officially-incorporates-nmr-method-in-compendium-of-international-methods-of-analysis-of-wines-and-musts.html" }, { "name": "OIV — OIV-OENO 618-2020", "url": "https://www.oiv.int/public/medias/7590/oiv-oeno-618-2020-en.pdf" } ] }, { "id": 137, "catalogId": 141, "slug": "oritain-137", "url": "https://vinumexmachina.com/casebook/cases/#case-137", "nameRu": "Oritain", "nameEn": "Oritain", "operatorRu": "Pyramid Valley Winery", "operatorEn": "Pyramid Valley Winery", "countryRu": "Новая Зеландия", "countryEn": "New Zealand", "domain": "winemaking", "tech": "chemometrics", "stage": "commercial", "country": [ "nz" ], "confidence": "b", "aiKind": "yes", "techRu": "Микроэлементный и изотопный «отпечаток происхождения» + статистические модели", "techEn": "Trace-element and isotopic \"origin fingerprint\" + statistical models", "doesRu": "Верификация происхождения через QR-код на бутылке", "doesEn": "Origin verification via a QR code on the bottle", "resultsRu": "Партнёрство с 2022, начиная с урожая 2020", "resultsEn": "Partnership since 2022, starting with the 2020 harvest", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Decanter", "url": "https://www.decanter.com/wine-news/nz-winery-fingerprint-verify-fine-wine-origin-489923/" } ] }, { "id": 138, "catalogId": 142, "slug": "m-wine-138", "url": "https://vinumexmachina.com/casebook/cases/#case-138", "nameRu": "M&Wine", "nameEn": "M&Wine", "operatorRu": "Производители и негоцианты", "operatorEn": "Producers and négociants", "countryRu": "Франция (Лион)", "countryEn": "France (Lyon)", "domain": "winemaking", "tech": "chemometrics", "stage": "pilot", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Анализ мультиминеральной сигнатуры вина", "techEn": "Analysis of a wine's multi-mineral signature", "doesRu": "«Паспорт» вина для защиты от подделок; проводился слепой тест против сомелье", "doesEn": "A wine \"passport\" to protect against counterfeits; a blind test against sommeliers was run", "resultsRu": "€400 000 привлечено в 2023, грант French Tech €78 000; 7 000+ бутылок проанализировано к апрелю 2023, цель — 50 000.", "resultsEn": "€400,000 raised in 2023, a French Tech grant of €78,000; 7,000+ bottles analysed by April 2023, the target is 50,000.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2023, "yearDisplay": "2021–2023", "yearRaw": "2021–2023", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Lyon Décideurs", "url": "https://lyondecideurs.com/2023/04/actu/mwine-la-start-up-qui-dresse-ladn-des-vins/" } ] }, { "id": 139, "catalogId": 143, "slug": "m-a-silva-bionic-eye-139", "url": "https://vinumexmachina.com/casebook/cases/#case-139", "nameRu": "M.A. Silva «Bionic Eye»", "nameEn": "M.A. Silva \"Bionic Eye\"", "operatorRu": "Производитель корковых пробок", "operatorEn": "Cork stopper producer", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "winemaking", "tech": "cv", "stage": "commercial", "country": [ "pt" ], "confidence": "a", "aiKind": "yes", "techRu": "Компьютерное зрение, 12 проверок на каждую пробку", "techEn": "Computer vision, 12 checks on every cork", "doesRu": "Выявление риска ТСА, трещин, загрязнений, ходов насекомых", "doesEn": "Detection of TCA risk, cracks, contamination and insect tunnels", "resultsRu": "Стабильность человеческого контроля ~75% против ~100% у системы; пропускная способность до 40 000 пробок в час; каждая проверка независимо логируется.", "resultsEn": "Consistency of human inspection ~75% against ~100% for the system; throughput up to 40,000 corks per hour; every check is logged independently.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2026/07/how-artificial-intelligence-is-safeguarding-a-millennia-old-practice/" } ] }, { "id": 140, "catalogId": 144, "slug": "dtwine-140", "url": "https://vinumexmachina.com/casebook/cases/#case-140", "nameRu": "DTWINE", "nameEn": "DTWINE", "operatorRu": "IATA-CSIC, IIM-CSIC, Bodega Ramón Bilbao, INCONEF", "operatorEn": "IATA-CSIC, IIM-CSIC, Bodega Ramón Bilbao, INCONEF", "countryRu": "Испания", "countryEn": "Spain", "domain": "winemaking", "tech": "sensors-iot", "stage": "pilot", "country": [ "es" ], "confidence": "a", "aiKind": "yes", "techRu": "Цифровой двойник ферментации на 30-литровых сенсорных ёмкостях", "techEn": "Digital twin of fermentation on 30-litre sensor-equipped vessels", "doesRu": "Симуляция и оптимизация брожения в реальном времени", "doesEn": "Real-time simulation and optimisation of fermentation", "resultsRu": "€1 млн бюджета, 36 месяцев; проект охватывает 4 винных региона Испании, а экспериментальная винодельня — одна пилотная установка в Валенсии.", "resultsEn": "€1m budget, 36 months; the project covers 4 Spanish wine regions, while the experimental winery is a single pilot plant in Valencia.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2024, "yearDisplay": "2021–2024", "yearRaw": "2021–2024", "sectionKey": "B", "sectionRu": "B. 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Виноделие и лаборатория", "sources": [ { "name": "HIGHFIVE", "url": "https://ss4af.com/en/highfive/projects/wine-pro-digital-twin-wine-fermentation-process-optimisation" } ] }, { "id": 142, "catalogId": 146, "slug": "tailored-wine-iim-csic-142", "url": "https://vinumexmachina.com/casebook/cases/#case-142", "nameRu": "Tailored-Wine (IIM-CSIC)", "nameEn": "Tailored-Wine (IIM-CSIC)", "operatorRu": "Ранняя стадия исследования", "operatorEn": "Early-stage research", "countryRu": "Испания", "countryEn": "Spain", "domain": "winemaking", "tech": "chemometrics", "stage": "research", "country": [ "es" ], "confidence": "b", "aiKind": "yes", "techRu": "Гибридные механистические + ИИ-модели метаболизма дрожжей", "techEn": "Hybrid mechanistic + AI models of yeast metabolism", "doesRu": "Прогноз и управление исходом ферментации", "doesEn": "Prediction and control of the fermentation outcome", "resultsRu": "Результатов пока нет.", "resultsEn": "No results yet.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "B", "sectionRu": "B. 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Виноделие и лаборатория", "sources": [ { "name": "Wine Intelligence", "url": "https://wine-intelligence.com/blogs/wine-news-insights-wine-intelligence-trends-data-reports/enartis-to-acquire-parsec-a-strategic-step-toward-integrated-winemaking-technologies" } ] }, { "id": 144, "catalogId": 148, "slug": "vivelys-scalya-oeneo-144", "url": "https://vinumexmachina.com/casebook/cases/#case-144", "nameRu": "Vivelys Scalya (OENEO)", "nameEn": "Vivelys Scalya (OENEO)", "operatorRu": "Клиенты группы OENEO", "operatorEn": "Customers of the OENEO group", "countryRu": "Весь мир", "countryEn": "International", "domain": "winemaking", "tech": "sensors-iot", "stage": "commercial", "country": [ "international" ], "confidence": "c", "aiKind": "borderline", "techRu": "Автоматизация ферментации и мацерации по датчикам", "techEn": "Sensor-driven automation of fermentation and maceration", "doesRu": "Управление шапкой, температурой, экстракцией", "doesEn": "Control of the cap, the temperature and extraction", "resultsRu": "ML-компонент в открытых материалах не подтверждён.", "resultsEn": "An ML component is not confirmed in public materials.", "caveatRu": "", "caveatEn": "", "whyRu": "Сенсорное управление ферментацией; обучаемого компонента вендор не заявляет.", "whyEn": "Sensor-based control of fermentation; the vendor does not claim a learning component.", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "B", "sectionRu": "B. 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Виноделие и лаборатория", "sources": [ { "name": "Pellenc", "url": "https://www.pellenc.com/fr-fr/nos-produits/de-la-vigne-a-la-cave/viniculture/reception/integral-vision" } ] }, { "id": 146, "catalogId": 150, "slug": "ferrari-trento-146", "url": "https://vinumexmachina.com/casebook/cases/#case-146", "nameRu": "Ferrari Trento", "nameEn": "Ferrari Trento", "operatorRu": "Ferrari Trento (Trentodoc)", "operatorEn": "Ferrari Trento (Trentodoc)", "countryRu": "Италия", "countryEn": "Italy", "domain": "winemaking", "tech": "cv", "stage": "commercial", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "Глубокое обучение на конвейере приёмки, QR-маркированные ящики", "techEn": "Deep learning on the intake line, QR-tagged crates", "doesRu": "Контроль качества винограда от 700+ хозяйств-поставщиков", "doesEn": "Quality control of grapes from 700+ supplier estates", "resultsRu": "Премия SMAU Innovation 2021; точность не раскрыта.", "resultsEn": "SMAU Innovation Award 2021; accuracy not disclosed.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "2021", "yearRaw": "2021", "sectionKey": "B", "sectionRu": "B. 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Виноделие и лаборатория", "sources": [ { "name": "Hochschule Trier", "url": "https://www.hochschule-trier.de/hochschule/aktuelles/news-und-pressemitteilungen/news-detail/kuenstliche-intelligenz-im-weinbau" } ] }, { "id": 152, "catalogId": 156, "slug": "codorniu-tsifrovoy-dvoynik-eurecat-152", "url": "https://vinumexmachina.com/casebook/cases/#case-152", "nameRu": "Codorníu (цифровой двойник, Eurecat)", "nameEn": "Codorníu (digital twin, Eurecat)", "operatorRu": "Codorníu", "operatorEn": "Codorníu", "countryRu": "Испания", "countryEn": "Spain", "domain": "winemaking", "tech": "optimisation", "stage": "pilot", "country": [ "es" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-двойник производства", "techEn": "AI twin of production", "doesRu": "Симуляция производственных процессов", "doesEn": "Simulation of production processes", "resultsRu": "Показан на Wine Innovation Week 2026, результатов нет.", "resultsEn": "Shown at Wine Innovation Week 2026; no results.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "B", "sectionRu": "B. Виноделие и лаборатория", "sources": [ { "name": "Interempresas", "url": "https://www.interempresas.net/Vitivinicola/624507-Wine-Innovation-Week-2026-confirma-inteligencia-artificial-motor-transformacion-vino.html" } ] }, { "id": 153, "catalogId": 157, "slug": "vivino-153", "url": "https://vinumexmachina.com/casebook/cases/#case-153", "nameRu": "Vivino", "nameEn": "Vivino", "operatorRu": "Потребители", "operatorEn": "Consumers", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "cv", "stage": "scaled", "country": [ "international" ], "confidence": "a", "aiKind": "yes", "techRu": "Распознавание этикеток + OCR + рекомендательный алгоритм на краудданных", "techEn": "Label recognition + OCR + recommendation algorithm on crowd data", "doesRu": "Определяет вино по фото и подбирает под вкус пользователя", "doesEn": "Identifies a wine from a photo and matches it to the user's taste", "resultsRu": "74 млн+ пользователей (2026); 3,26 млрд+ отсканированных этикеток; 19,6 млн+ вин в базе; 300 млн оценок. Комиссия маркетплейса 15%. Ни одного прибыльного квартала за всю историю.", "resultsEn": "74m+ users (2026); 3.26bn+ labels scanned; 19.6m+ wines in the database; 300m ratings. Marketplace commission 15%. Not a single profitable quarter in its history.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2010, "yearEnd": 2026, "yearDisplay": "2010–2026", "yearRaw": "2010–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Expanded Ramblings", "url": "https://expandedramblings.com/index.php/vivino-facts-statistics/" }, { "name": "Meininger's", "url": "https://www.meininger.de/wein/handel/vivino-die-millionen-app" } ] }, { "id": 154, "catalogId": 158, "slug": "issledovanie-kembridzha-kraudotsenki-protiv-154", "url": "https://vinumexmachina.com/casebook/cases/#case-154", "nameRu": "Исследование в Journal of Wine Economics: краудоценки против критиков", "nameEn": "Journal of Wine Economics study: crowd ratings versus critics", "operatorRu": "Journal of Wine Economics", "operatorEn": "Journal of Wine Economics", "countryRu": "Франция", "countryEn": "France", "domain": "business", "tech": "recommender", "stage": "research", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Корреляционный анализ", "techEn": "Correlation analysis", "doesRu": "Сравнение оценок Vivino с профессиональными критиками по Бордо 2004–2016", "doesEn": "Comparison of Vivino ratings with professional critics for Bordeaux 2004–2016", "resultsRu": "Средняя корреляция Vivino с критиками 40% при средней корреляции каждого критика с остальными участниками сравнения от 46% до 63%; лучшее совпадение с Vivino — Wine Advocate (50%), худшее — Decanter (16%)", "resultsEn": "Average correlation of Vivino with critics 40%, against 46% to 63% for each critic's average correlation with the others in the comparison; best match with Vivino the Wine Advocate (50%), worst Decanter (16%)", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Journal of Wine Economics", "url": "https://doi.org/10.1017/jwe.2024.20" } ] }, { "id": 155, "catalogId": 159, "slug": "liv-ex-155", "url": "https://vinumexmachina.com/casebook/cases/#case-155", "nameRu": "Liv-ex", "nameEn": "Liv-ex", "operatorRu": "Биржа тонких вин", "operatorEn": "Fine wine exchange", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "international" ], "confidence": "a", "aiKind": "yes", "techRu": "Персонализация, автоматическое ценообразование, генерация рыночной аналитики", "techEn": "Personalisation, automated pricing, generation of market analytics", "doesRu": "Перестройка платформы вокруг ИИ", "doesEn": "Rebuilding the platform around AI", "resultsRu": "По данным самого Liv-ex, 500+ участников из 42 стран; заявленная цель — оценка погреба «с часов до секунд»", "resultsEn": "According to Liv-ex itself, 500+ members from 42 countries; the stated aim is cellar valuation \"from hours to seconds\"", "caveatRu": "Число участников приводится по странице самого Liv-ex; в цитируемой статье этой цифры нет.", "caveatEn": "The membership figure is given from Liv-ex's own page; the cited article does not contain it.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2026/03/liv-ex-ai-will-filter-out-the-noise-to-provide-more-relevant-fine-wine-data/" } ] }, { "id": 156, "catalogId": 160, "slug": "vinovest-156", "url": "https://vinumexmachina.com/casebook/cases/#case-156", "nameRu": "Vinovest", "nameEn": "Vinovest", "operatorRu": "Инвесторы в тонкие вина", "operatorEn": "Fine wine investors", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "recommender", "stage": "ended", "country": [ "international" ], "confidence": "a", "aiKind": "yes", "techRu": "«Робоэдвайзер» на собственном алгоритме", "techEn": "\"Robo-adviser\" on a proprietary algorithm", "doesRu": "Подбор объектов инвестирования под профиль риска", "doesEn": "Selection of investments to match a risk profile", "resultsRu": "Более $100 млн активов под управлением и 250 000 пользователей (Whisky Magazine). Покупка StartEngine закрыта 17 марта 2026 года, выпущено 8 750 000 акций.", "resultsEn": "More than $100m in assets under management and 250,000 users (Whisky Magazine). The StartEngine purchase closed on 17 March 2026, with 8,750,000 shares issued.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2025, "yearDisplay": "2021–2025", "yearRaw": "2021–2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Whisky Magazine", "url": "https://www.whiskymag.com/articles/vinovest-meet-the-tech-entrepreneur-managing-more-than-100-million-in-whisky-and-fine-wine-investments/" }, { "name": "Vinovest", "url": "https://www.vinovest.co/blog/startengine-acquires-vinovest-to-broaden-access-to-alternative-assets" } ] }, { "id": 157, "catalogId": 161, "slug": "cultx-cult-wines-157", "url": "https://vinumexmachina.com/casebook/cases/#case-157", "nameRu": "CultX (Cult Wines)", "nameEn": "CultX (Cult Wines)", "operatorRu": "Коллекционеры и инвесторы", "operatorEn": "Collectors and investors", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "gb" ], "confidence": "a", "aiKind": "yes", "techRu": "ИИ-фильтрация по бюджету и стилю, скоринг ликвидности по данным сделок", "techEn": "AI filtering by budget and style, liquidity scoring from transaction data", "doesRu": "Торговая платформа тонких вин", "doesEn": "Fine wine trading platform", "resultsRu": "6 000 живых рынков; число сделок +7,2% в 2025 к 2024 при падении средних цен на 5,6%", "resultsEn": "6,000 live markets; number of transactions +7.2% in 2025 against 2024, with average prices falling 5.6%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Decanter", "url": "https://www.decanter.com/magazine/a-drink-with-tom-gearing-on-cultx-and-ai-in-the-wine-market/" } ] }, { "id": 158, "catalogId": 162, "slug": "e-j-gallo-aera-technology-158", "url": "https://vinumexmachina.com/casebook/cases/#case-158", "nameRu": "E&J Gallo + Aera Technology", "nameEn": "E&J Gallo + Aera Technology", "operatorRu": "E&J Gallo", "operatorEn": "E&J Gallo", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Агентный ИИ поверх ERP", "techEn": "Agentic AI on top of ERP", "doesRu": "Автоматизация маршрутизации прямых отгрузок, перебалансировки запасов, управления просроченными остатками", "doesEn": "Automation of direct-shipment routing, inventory rebalancing and overdue-stock management", "resultsRu": "$890 000 экономии в первый год, окупаемость около года; 5 сценариев, ~3 месяца на внедрение каждого; первый запуск в феврале 2025", "resultsEn": "$890,000 saved in the first year, payback about a year; 5 scenarios, ~3 months to deploy each; first go-live in February 2025", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Forbes", "url": "https://www.forbes.com/sites/stevebanker/2026/06/10/gallo-invests-in-agentic-ai-to-improve-supply-chain-capabilities/" } ] }, { "id": 159, "catalogId": 163, "slug": "constellation-brands-blue-yonder-159", "url": "https://vinumexmachina.com/casebook/cases/#case-159", "nameRu": "Constellation Brands + Blue Yonder", "nameEn": "Constellation Brands + Blue Yonder", "operatorRu": "Constellation (Robert Mondavi, Kim Crawford, Meiomi, The Prisoner, Ruffino)", "operatorEn": "Constellation (Robert Mondavi, Kim Crawford, Meiomi, The Prisoner, Ruffino)", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Предиктивный прогноз спроса и планирование полочного пространства", "techEn": "Predictive demand forecasting and shelf-space planning", "doesRu": "Замена планирования по историческим продажам на ML", "doesEn": "Replaces planning based on historical sales with ML", "resultsRu": "Рост продаж категории до 6%, снижение out-of-stock", "resultsEn": "Category sales growth of up to 6%, reduction in out-of-stocks", "caveatRu": "«До 6%» — максимум, а не среднее; цифра приводится вендором и независимо не подтверждена.", "caveatEn": "\"Up to 6%\" is a maximum, not an average; the figure is given by the vendor and is not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Blue Yonder", "url": "https://blueyonder.com/customers/constellation-brands" } ] }, { "id": 160, "catalogId": 164, "slug": "treasury-wine-estates-innovation-engine-160", "url": "https://vinumexmachina.com/casebook/cases/#case-160", "nameRu": "Treasury Wine Estates «Innovation Engine»", "nameEn": "Treasury Wine Estates \"Innovation Engine\"", "operatorRu": "Treasury Americas (Cali by Snoop, 19 Crimes, Matua Bagnum)", "operatorEn": "Treasury Americas (Cali by Snoop, 19 Crimes, Matua Bagnum)", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-платформа сокреации продукта с онлайн-панелями потребителей", "techEn": "AI product co-creation platform with online consumer panels", "doesRu": "Кластеризация обратной связи в темы для разработки", "doesEn": "Clusters feedback into themes for development", "resultsRu": "Цикл разработки сокращён с 12–18 месяцев до менее чем 6; MVP за 87 дней против прежних 180; повторные покупки Cali by Snoop превысили целевые 20%; топ-10 среди новых запусков по данным Circana.", "resultsEn": "Development cycle cut from 12–18 months to under 6; MVP in 87 days against 180 previously; repeat purchases of Cali by Snoop exceeded the 20% target; top 10 among new launches according to Circana.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2026, "yearDisplay": "2024–2026", "yearRaw": "2024–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Forbes", "url": "https://www.forbes.com/sites/lizthach/2026/04/09/how-treasury-wine-estates-is-leveraging-ai-to-create-wines-consumers-love/" } ] }, { "id": 161, "catalogId": 165, "slug": "pernod-ricard-161", "url": "https://vinumexmachina.com/casebook/cases/#case-161", "nameRu": "Pernod Ricard", "nameEn": "Pernod Ricard", "operatorRu": "Pernod Ricard", "operatorEn": "Pernod Ricard", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "optimisation", "stage": "scaled", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "Прогноз потребительского поведения, перераспределение маркетингового бюджета в реальном времени, рекомендации торговым представителям", "techEn": "Consumer behaviour forecasting, real-time reallocation of the marketing budget, recommendations for sales representatives", "doesRu": "Управление портфелем из 240 брендов", "doesEn": "Management of a portfolio of 240 brands", "resultsRu": "Годовой маркетинговый бюджет около €1,5 млрд, из которых примерно 80% распределяется этими моделями, по 240 брендам.", "resultsEn": "Annual marketing budget of about €1.5bn, of which roughly 80% is allocated by these models, across 240 brands.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2026, "yearDisplay": "2024–2026", "yearRaw": "2024–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2024/06/ai-is-here-to-help-make-better-decisions-for-wine-trade/" } ] }, { "id": 162, "catalogId": 166, "slug": "diageo-strategy-microstrategy-162", "url": "https://vinumexmachina.com/casebook/cases/#case-162", "nameRu": "Diageo + Strategy (MicroStrategy)", "nameEn": "Diageo + Strategy (MicroStrategy)", "operatorRu": "Diageo", "operatorEn": "Diageo", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "international" ], "confidence": "c", "aiKind": "yes", "techRu": "ИИ-агенты, автогенерируемые дашборды, сценарное моделирование", "techEn": "AI agents, auto-generated dashboards, scenario modelling", "doesRu": "Прогноз спроса, ценообразование, выявление аномалий", "doesEn": "Demand forecasting, pricing, anomaly detection", "resultsRu": "Ускорение расчётов на 25%; доступность данных 96%. Отдельно: Diageo работает примерно в 180 странах.", "resultsEn": "Calculations 25% faster; data availability 96%. Separately: Diageo operates in about 180 countries.", "caveatRu": "«Около 180 стран» — отдельный факт о географии Diageo; с показателем доступности данных источник его не связывает.", "caveatEn": "\"About 180 countries\" is a separate fact about Diageo's geography; the source does not link it to the data-availability figure.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Strategy", "url": "https://software.strategy.com/customer-stories/diageo" } ] }, { "id": 163, "catalogId": 167, "slug": "diageo-vivanda-flavorprint-163", "url": "https://vinumexmachina.com/casebook/cases/#case-163", "nameRu": "Diageo / Vivanda FlavorPrint", "nameEn": "Diageo / Vivanda FlavorPrint", "operatorRu": "Diageo", "operatorEn": "Diageo", "countryRu": "Китай, Великобритания, Индия", "countryEn": "China, United Kingdom, India", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "cn", "gb", "in" ], "confidence": "b", "aiKind": "yes", "techRu": "Алгоритмическое сопоставление вкусовых предпочтений", "techEn": "Algorithmic matching of taste preferences", "doesRu": "Персональные рекомендации по портфелю", "doesEn": "Personal recommendations across the portfolio", "resultsRu": "Vivanda поглощена Diageo; локализованные версии запущены в Китае и Индии.", "resultsEn": "Vivanda was acquired by Diageo; localised versions launched in China and India.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": null, "yearDisplay": "2022–", "yearRaw": "2022–", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/08/ways-alcoholic-drinks-retailing-getting-smarter/" } ] }, { "id": 164, "catalogId": 168, "slug": "lvmh-google-cloud-164", "url": "https://vinumexmachina.com/casebook/cases/#case-164", "nameRu": "LVMH × Google Cloud", "nameEn": "LVMH × Google Cloud", "operatorRu": "LVMH, включая Moët Hennessy", "operatorEn": "LVMH, including Moët Hennessy", "countryRu": "Франция", "countryEn": "France", "domain": "business", "tech": "optimisation", "stage": "research", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "Прогноз спроса, персональные предложения", "techEn": "Demand forecasting, personalised offers", "doesRu": "Пятилетнее стратегическое партнёрство, совместная «Академия данных и ИИ»", "doesEn": "Five-year strategic partnership, a joint \"Data and AI Academy\"", "resultsRu": "Общекорпоративные показатели LVMH: вино и крепкий алкоголь — 7% выручки; продажи направления в первом квартале 2021 выросли на 29%.", "resultsEn": "Group-wide LVMH figures: wines and spirits 7% of revenue; the division's sales rose 29% in the first quarter of 2021.", "caveatRu": "Партнёрство с Google Cloud — анонс; обе цифры относятся к LVMH в целом и с ИИ не связаны.", "caveatEn": "The Google Cloud partnership is an announcement; both figures relate to LVMH as a whole and are not connected to AI.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": null, "yearDisplay": "2021–", "yearRaw": "2021–", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2021/06/arnault-of-lvmh-partners-with-google-cloud-on-ai-project/" } ] }, { "id": 165, "catalogId": 169, "slug": "preferabli-165", "url": "https://vinumexmachina.com/casebook/cases/#case-165", "nameRu": "Preferabli", "nameEn": "Preferabli", "operatorRu": "Ретейл и рестораны", "operatorEn": "Retail and restaurants", "countryRu": "США, Великобритания", "countryEn": "United States, United Kingdom", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us", "gb" ], "confidence": "b", "aiKind": "yes", "techRu": "«Сенсорный ИИ» + генеративный чат-сомелье", "techEn": "\"Sensory AI\" + generative sommelier chat", "doesRu": "Персональные рекомендации и подбор к еде", "doesEn": "Personal recommendations and food pairing", "resultsRu": "15 патентов", "resultsEn": "15 patents", "caveatRu": "Источник подтверждает только число патентов; остальные показатели и названия клиентов в нём отсутствуют.", "caveatEn": "The source confirms only the number of patents; the other figures and the client names are absent from it.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/10/from-algorithms-to-appellations-the-rise-of-ai-in-wine/" } ] }, { "id": 166, "catalogId": 170, "slug": "drinks-pair-166", "url": "https://vinumexmachina.com/casebook/cases/#case-166", "nameRu": "Drinks «PAIR»", "nameEn": "Drinks \"PAIR\"", "operatorRu": "E-commerce алкоголя", "operatorEn": "Alcohol e-commerce", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "ИИ анализирует дизайн этикетки для прогноза эмоциональной реакции", "techEn": "AI analyses label design to predict emotional response", "doesRu": "Рекомендации на основе визуального восприятия", "doesEn": "Recommendations based on visual perception", "resultsRu": "По заявлению сооснователя компании, рост кликабельности более чем на 50% относительно стандартных рекомендаций", "resultsEn": "According to a statement by the company's co-founder, click-through up by more than 50% against standard recommendations", "caveatRu": "Цифра приводится по заявлению компании и независимо не подтверждена.", "caveatEn": "The figure is given from a company statement and is not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/04/are-consumers-ready-to-embrace-ai-powered-drinks-picks/" } ] }, { "id": 167, "catalogId": 171, "slug": "enolytics-167", "url": "https://vinumexmachina.com/casebook/cases/#case-167", "nameRu": "Enolytics", "nameEn": "Enolytics", "operatorRu": "Винодельни (DTC и опт)", "operatorEn": "Wineries (DTC and wholesale)", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Аналитика удержания винного клуба, сегментация, прогнозирование", "techEn": "Wine club retention analytics, segmentation, forecasting", "doesRu": "Управление прямыми продажами", "doesEn": "Management of direct sales", "resultsRu": "По клиентским отзывам, размещённым на сайте самой компании: средний рост DTC-продаж у клиентов 17,9% против 5,2% по отрасли; Black Ankle Vineyards — 85 ящиков на $60 000 за 24 часа через таргетированную сегментацию; Far Niente — +6% корпоративных подарочных продаж", "resultsEn": "According to client testimonials posted on the company's own site: average DTC sales growth among clients of 17.9% against 5.2% for the industry; Black Ankle Vineyards — 85 cases worth $60,000 in 24 hours through targeted segmentation; Far Niente — +6% in corporate gift sales", "caveatRu": "Все три показателя — клиентские отзывы, размещённые самим вендором; независимой проверки они не проходили.", "caveatEn": "All three figures are client testimonials posted by the vendor itself; they have not been independently verified.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2025, "yearDisplay": "2023–2025", "yearRaw": "2023–2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Enolytics", "url": "https://enolytics.com/" } ] }, { "id": 168, "catalogId": 172, "slug": "hawesko-group-gk-software-nexum-168", "url": "https://vinumexmachina.com/casebook/cases/#case-168", "nameRu": "Hawesko Group (GK Software + nexum)", "nameEn": "Hawesko Group (GK Software + nexum)", "operatorRu": "Hawesko.de, Vinos.de, Tesdorpf.de", "operatorEn": "Hawesko.de, Vinos.de, Tesdorpf.de", "countryRu": "Германия", "countryEn": "Germany", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "de" ], "confidence": "c", "aiKind": "yes", "techRu": "Рекомендательный движок", "techEn": "Recommendation engine", "doesRu": "Персонализация витрины, CRM и кампаний", "doesEn": "Personalisation of the storefront, CRM and campaigns", "resultsRu": "До 12% выше маржа на бутылку в A/B-тесте; каталог 8 500 вин", "resultsEn": "Up to 12% higher margin per bottle in an A/B test; catalogue of 8,500 wines", "caveatRu": "Цифры приводятся в кейсе вендора; «до 12%» — максимум в A/B-тесте, а не средний результат.", "caveatEn": "The figures are given in the vendor's case study; \"up to 12%\" is the maximum in the A/B test, not the average result.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "nexum", "url": "https://www.nexum.com/de/cases/hawesko" } ] }, { "id": 169, "catalogId": 173, "slug": "dein-weinfreund-169", "url": "https://vinumexmachina.com/casebook/cases/#case-169", "nameRu": "«Dein Weinfreund»", "nameEn": "\"Dein Weinfreund\"", "operatorRu": "Weinfreunde.de", "operatorEn": "Weinfreunde.de", "countryRu": "Германия", "countryEn": "Germany", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "de" ], "confidence": "c", "aiKind": "yes", "techRu": "LLM-чат-советник", "techEn": "LLM chat adviser", "doesRu": "Подбор вина по вкусу и поводу без регистрации", "doesEn": "Wine selection by taste and occasion without registration", "resultsRu": "1 000+ товаров; работает с 1 сентября 2024.", "resultsEn": "1,000+ products; running since 1 September 2024.", "caveatRu": "Цифра приводится по заявлению компании и независимо не подтверждена.", "caveatEn": "The figure is given from a company statement and is not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Weinfreunde", "url": "https://www.weinfreunde.de/magazin/presse/weinfreunde-de-hilft-bei-der-suche-nach-dem-passenden-wein-ki-loesung-dein-weinfreund-schafft-ein-neues-kauferlebnis/" } ] }, { "id": 170, "catalogId": 174, "slug": "vinolin-170", "url": "https://vinumexmachina.com/casebook/cases/#case-170", "nameRu": "Vinolin", "nameEn": "Vinolin", "operatorRu": "15 виноделен и кооперативов, включая Heilbronn Cooperative Cellar", "operatorEn": "15 wineries and cooperatives, including Heilbronn Cooperative Cellar", "countryRu": "Германия", "countryEn": "Germany", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "de" ], "confidence": "b", "aiKind": "yes", "techRu": "LLM-чат-бот внутри магазина винодельни", "techEn": "LLM chatbot inside the winery's shop", "doesRu": "Рекомендации строго из собственного ассортимента партнёра, круглосуточно", "doesEn": "Recommendations strictly from the partner's own range, around the clock", "resultsRu": "Гранты €160 000 (министерство Штутгарта) и €40 000 (Campus Founders); команда из 4 человек", "resultsEn": "Grants of €160,000 (Stuttgart ministry) and €40,000 (Campus Founders); a team of 4", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Stuttgarter Nachrichten", "url": "https://www.stuttgarter-nachrichten.de/inhalt.neues-start-up-wenn-die-ki-den-wein-empfiehlt.acad2068-dc71-41b5-9892-7ccf72b36b68.html" } ] }, { "id": 171, "catalogId": 175, "slug": "winesecret-171", "url": "https://vinumexmachina.com/casebook/cases/#case-171", "nameRu": "WineSecret", "nameEn": "WineSecret", "operatorRu": "Онлайн-ретейлеры и дистрибьюторы", "operatorEn": "Online retailers and distributors", "countryRu": "Китай (Гонконг)", "countryEn": "China (Hong Kong)", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-чат-бот плюс аналитика продаж, запасов и POS", "techEn": "AI chatbot plus sales, inventory and POS analytics", "doesRu": "Бэкенд для онлайн-магазинов", "doesEn": "Back end for online shops", "resultsRu": "~1 000 конечных пользователей на старте; подписка от 4 166 гонконгских долларов в месяц", "resultsEn": "~1,000 end users at launch; subscription from 4,166 Hong Kong dollars a month", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2026/01/is-hong-kongs-wine-sector-slow-on-the-ai-uptake/" } ] }, { "id": 172, "catalogId": 176, "slug": "firstleaf-penrose-hill-172", "url": "https://vinumexmachina.com/casebook/cases/#case-172", "nameRu": "Firstleaf (Penrose Hill)", "nameEn": "Firstleaf (Penrose Hill)", "operatorRu": "Подписчики винного клуба", "operatorEn": "Wine club subscribers", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Нейросеть на оценках подписчиков", "techEn": "Neural network on subscriber ratings", "doesRu": "Персональный подбор ежемесячной подборки", "doesEn": "Personal matching of the monthly selection", "resultsRu": "Компания заявляет, что 92% отобранных вин имеют конкурсные награды.", "resultsEn": "The company claims that 92% of the wines selected hold competition awards.", "caveatRu": "92% — заявление компании из пресс-релиза 2018 года; независимого подтверждения нет.", "caveatEn": "The 92% is a company claim from a 2018 press release; there is no independent confirmation.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2026, "yearDisplay": "2018–2026", "yearRaw": "2018–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "PR Newswire", "url": "https://www.prnewswire.com/news-releases/firstleaf-debuts-new-algorithm-to-enhance-the-customization-of-wine-selections-300658718.html" } ] }, { "id": 173, "catalogId": 177, "slug": "bright-cellars-173", "url": "https://vinumexmachina.com/casebook/cases/#case-173", "nameRu": "Bright Cellars", "nameEn": "Bright Cellars", "operatorRu": "Подписчики винного клуба", "operatorEn": "Wine club subscribers", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Алгоритм «Bright Points»: 18 атрибутов против опроса из 7 вопросов", "techEn": "\"Bright Points\" algorithm: 18 attributes against a 7-question survey", "doesRu": "Подбор вина под вкусовой профиль", "doesEn": "Matching wine to a taste profile", "resultsRu": "600 000+ пятизвёздочных оценок накоплено.", "resultsEn": "600,000+ five-star ratings accumulated.", "caveatRu": "Цифра приводится по данным самой компании и независимо не подтверждена.", "caveatEn": "The figure is given from the company itself and is not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2015, "yearEnd": 2026, "yearDisplay": "2015–2026", "yearRaw": "2015–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Bright Cellars", "url": "https://www.brightcellars.com/pages/about-us" } ] }, { "id": 174, "catalogId": 178, "slug": "winc-bankrotstvo-174", "url": "https://vinumexmachina.com/casebook/cases/#case-174", "nameRu": "Winc — банкротство", "nameEn": "Winc — bankruptcy", "operatorRu": "Винный клуб по подписке", "operatorEn": "Wine subscription club", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "ended", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "Персонализация через опрос «Palate Profile»", "techEn": "Personalisation through the \"Palate Profile\" survey", "doesRu": "Подбор вина по вкусовому профилю", "doesEn": "Matching wine to a taste profile", "resultsRu": "Рост выручки на 77,5% в пандемию (2019–2020) оказался неустойчивым; выручка DTC в третьем квартале 2022 упала на $2,8 млн. Глава 11 в ноябре 2022: долги $36,75 млн против активов $50,3 млн.", "resultsEn": "Revenue growth of 77.5% during the pandemic (2019–2020) proved unsustainable; DTC revenue in the third quarter of 2022 fell by $2.8m. Chapter 11 in November 2022: debts of $36.75m against assets of $50.3m.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2011, "yearEnd": 2022, "yearDisplay": "2011–2022", "yearRaw": "2011–2022", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2022/12/online-wine-membership-club-winc-files-for-bankruptcy/" }, { "name": "SEC, Form 8-K", "url": "https://www.sec.gov/Archives/edgar/data/1782627/000095017022025906/wbev-20221130.htm" } ] }, { "id": 175, "catalogId": 179, "slug": "sippd-175", "url": "https://vinumexmachina.com/casebook/cases/#case-175", "nameRu": "Sippd", "nameEn": "Sippd", "operatorRu": "Потребители, партнёры-рестораны", "operatorEn": "Consumers, restaurant partners", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Скор «Taste Match» от 1 до 100 + распознавание винных карт", "techEn": "\"Taste Match\" score from 1 to 100 + wine list recognition", "doesRu": "Подбор по вкусовому профилю", "doesEn": "Matching by taste profile", "resultsRu": "Каталог из 10 000+ вин", "resultsEn": "Catalogue of 10,000+ wines", "caveatRu": "Цифра взята из пускового пресс-релиза компании и независимо не подтверждена.", "caveatEn": "The figure is taken from the company's launch press release and is not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "2021", "yearRaw": "2021", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Wine Industry Advisor", "url": "https://wineindustryadvisor.com/2021/03/19/sippd-launches-ai-powered-wine-app/" } ] }, { "id": 176, "catalogId": 180, "slug": "chai-wine-vault-maureen-downey-everledger-176", "url": "https://vinumexmachina.com/casebook/cases/#case-176", "nameRu": "Chai Wine Vault (Maureen Downey × Everledger)", "nameEn": "Chai Wine Vault (Maureen Downey × Everledger)", "operatorRu": "Трейдеры, ретейлеры, аукционные дома", "operatorEn": "Traders, retailers, auction houses", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "other", "stage": "commercial", "country": [ "international" ], "confidence": "a", "aiKind": "adjacent", "techRu": "Блокчейн-реестр провенанса", "techEn": "Blockchain provenance ledger", "doesRu": "Цифровой паспорт бутылки", "doesEn": "Digital passport for a bottle", "resultsRu": "90+ параметров данных плюс фотографии высокого разрешения на бутылку или ящик", "resultsEn": "90+ data parameters plus high-resolution photographs per bottle or case", "caveatRu": "", "caveatEn": "", "whyRu": "Блокчейн-реестр провенанса. Смежная технология прослеживаемости.", "whyEn": "Blockchain provenance ledger. Adjacent traceability technology.", "dataRu": "", "dataEn": "", "yearStart": 2016, "yearEnd": 2016, "yearDisplay": "2016", "yearRaw": "2016", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2016/11/maureen-downey-launches-fine-wine-tracker/" } ] }, { "id": 177, "catalogId": 181, "slug": "prosecco-doc-ai-brand-protection-177", "url": "https://vinumexmachina.com/casebook/cases/#case-177", "nameRu": "Prosecco DOC AI Brand Protection", "nameEn": "Prosecco DOC AI Brand Protection", "operatorRu": "Consorzio Tutela Prosecco DOC, Microsoft Italia, Istituto Poligrafico", "operatorEn": "Consorzio Tutela Prosecco DOC, Microsoft Italia, Istituto Poligrafico", "countryRu": "Италия", "countryEn": "Italy", "domain": "business", "tech": "llm", "stage": "pilot", "country": [ "it" ], "confidence": "a", "aiKind": "yes", "techRu": "Генеративный ИИ на Azure OpenAI", "techEn": "Generative AI on Azure OpenAI", "doesRu": "Защита наименования от подделок", "doesEn": "Protection of the appellation against counterfeits", "resultsRu": "Масштаб наименования: общий выпуск Prosecco DOC в 2023 году — около 616 млн бутылок, 81% на экспорт", "resultsEn": "Scale of the appellation: total Prosecco DOC output in 2023 was about 616m bottles, 81% for export", "caveatRu": "Это весь выпуск Prosecco DOC за 2023 год, а не объём, защищённый системой ИИ.", "caveatEn": "This is the whole Prosecco DOC output for 2023, not the volume protected by the AI system.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Prosecco DOC", "url": "https://www.prosecco.wine/en/ai-artificial-intelligenxe-to-protect-prosecco-doc/" } ] }, { "id": 178, "catalogId": 182, "slug": "aforza-178", "url": "https://vinumexmachina.com/casebook/cases/#case-178", "nameRu": "Aforza", "nameEn": "Aforza", "operatorRu": "Distell / Heineken Beverages", "operatorEn": "Distell / Heineken Beverages", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "za" ], "confidence": "c", "aiKind": "yes", "techRu": "ИИ-платформа полевых продаж и трейд-маркетинга", "techEn": "AI platform for field sales and trade marketing", "doesRu": "Единый профиль клиента, скоринг кредита в реальном времени, динамическое ценообразование", "doesEn": "Single customer profile, real-time credit scoring, dynamic pricing", "resultsRu": "По кейсу вендора, рост среднего чека и NPS в течение 8 месяцев после внедрения заявлен без цифр; компания — ~4 400 сотрудников и $1,8 млрд оборота.", "resultsEn": "According to the vendor's case study, growth in average order value and NPS within 8 months of deployment is claimed without figures; the company has ~4,400 employees and $1.8bn turnover.", "caveatRu": "Источник — кейс вендора: количественных показателей роста в нём нет, только качественные формулировки.", "caveatEn": "The source is a vendor case study: it contains no quantitative growth figures, only qualitative statements.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2024, "yearDisplay": "2023–2024", "yearRaw": "2023–2024", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Aforza", "url": "https://aforza.com/heineken-beverages/" } ] }, { "id": 179, "catalogId": 183, "slug": "winefi-lay-wheeler-179", "url": "https://vinumexmachina.com/casebook/cases/#case-179", "nameRu": "WineFi × Lay & Wheeler", "nameEn": "WineFi × Lay & Wheeler", "operatorRu": "Розничные инвесторы", "operatorEn": "Retail investors", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "gb" ], "confidence": "b", "aiKind": "yes", "techRu": "Алгоритмический подбор для инвестиционного синдиката", "techEn": "Algorithmic selection for an investment syndicate", "doesRu": "Формирование портфеля тонких вин", "doesEn": "Building a fine wine portfolio", "resultsRu": "WineFi привлекла £1,1 млн краудфандингом в 2025; минимальный вход £3 000, горизонт 5 лет.", "resultsEn": "WineFi raised £1.1m through crowdfunding in 2025; minimum entry £3,000, horizon 5 years.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/07/lay-wheeler-and-winefi-launch-fine-wine-investment-syndicate/" } ] }, { "id": 180, "catalogId": 184, "slug": "total-wine-more-180", "url": "https://vinumexmachina.com/casebook/cases/#case-180", "nameRu": "Total Wine & More", "nameEn": "Total Wine & More", "operatorRu": "Крупноформатный ретейл", "operatorEn": "Large-format retail", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Рекомендательные модели и навигация по залу", "techEn": "Recommendation models and in-store navigation", "doesRu": "Помощь в выборе в точке покупки", "doesEn": "Help with choosing at the point of purchase", "resultsRu": "«Тысячи вин» в ассортименте магазина", "resultsEn": "\"Thousands of wines\" in the store's range", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2024/06/ai-is-here-to-help-make-better-decisions-for-wine-trade/" } ] }, { "id": 181, "catalogId": 185, "slug": "tesco-clubcard-challenges-roambee-181", "url": "https://vinumexmachina.com/casebook/cases/#case-181", "nameRu": "Tesco (Clubcard Challenges + Roambee)", "nameEn": "Tesco (Clubcard Challenges + Roambee)", "operatorRu": "Супермаркет, винная категория", "operatorEn": "Supermarket, wine category", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "gb" ], "confidence": "c", "aiKind": "yes", "techRu": "Персонализация лояльности + ИИ-логистика", "techEn": "Loyalty personalisation + AI logistics", "doesRu": "Индивидуальные задания и награды покупателям", "doesEn": "Individual challenges and rewards for shoppers", "resultsRu": "4 250+ магазинов сети Tesco в Великобритании; 3 000 точек у Roambee", "resultsEn": "4,250+ Tesco stores in the United Kingdom; 3,000 sites at Roambee", "caveatRu": "4 250+ магазинов — это вся розничная сеть Tesco, а не винная категория и не охват ИИ.", "caveatEn": "4,250+ stores is the whole Tesco retail network, not the wine category and not the reach of the AI.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/08/ways-alcoholic-drinks-retailing-getting-smarter/" } ] }, { "id": 182, "catalogId": 186, "slug": "winespace-182", "url": "https://vinumexmachina.com/casebook/cases/#case-182", "nameRu": "Winespace", "nameEn": "Winespace", "operatorRu": "Concours Mondial de Bruxelles, кооператив Euralis", "operatorEn": "Concours Mondial de Bruxelles, the Euralis cooperative", "countryRu": "Франция, Бельгия", "countryEn": "France, Belgium", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "fr", "be" ], "confidence": "b", "aiKind": "yes", "techRu": "NLP-анализ дегустационных заметок", "techEn": "NLP analysis of tasting notes", "doesRu": "Стандартизация субъективной лексики на шести языках в визуальные ароматические профили", "doesEn": "Standardises subjective vocabulary in six languages into visual aroma profiles", "resultsRu": "База из ~12 000 винных оценок", "resultsEn": "A database of ~12,000 wine assessments", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2023, "yearDisplay": "2017–2023", "yearRaw": "2017–2023", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Union Girondine", "url": "https://www.union-girondine.com/winespace-decrypte-les-gouts-des-vins-au-profit-des-vignerons-et-consommateurs/" } ] }, { "id": 183, "catalogId": 187, "slug": "estandon-cooperative-183", "url": "https://vinumexmachina.com/casebook/cases/#case-183", "nameRu": "Estandon Cooperative", "nameEn": "Estandon Cooperative", "operatorRu": "Кооператив, Бриньоль", "operatorEn": "Cooperative, Brignoles", "countryRu": "Франция (Прованс)", "countryEn": "France (Provence)", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "Генеративный ИИ", "techEn": "Generative AI", "doesRu": "Поддержка HR, юридической функции, качества, закупок и продаж", "doesEn": "Supports HR, the legal function, quality, procurement and sales", "resultsRu": "Сокращений персонала не проводилось, инструмент позиционируется как «спарринг-партнёр».", "resultsEn": "No staff cuts were made; the tool is positioned as a “sparring partner”.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Réussir Vigne", "url": "https://www.reussir.fr/vigne/filiere-vitivinicole-ils-gagnent-du-temps-grace-lintelligence-artificielle" } ] }, { "id": 184, "catalogId": 188, "slug": "vinsuite-vinsight-184", "url": "https://vinumexmachina.com/casebook/cases/#case-184", "nameRu": "vinSUITE «vinSIGHT»", "nameEn": "vinSUITE “vinSIGHT”", "operatorRu": "Клиенты DTC/CRM-платформы", "operatorEn": "Clients of the DTC/CRM platform", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "us" ], "confidence": "c", "aiKind": "yes", "techRu": "Прогноз оттока членов винного клуба", "techEn": "Wine club member churn prediction", "doesRu": "Удержание клубной базы", "doesEn": "Retention of the club base", "resultsRu": "По данным вендора: «Отмечает членов клуба в зоне риска с уверенностью до 94% и объясняет, какие факторы влияют на оценку риска».", "resultsEn": "According to the vendor: “Flags at-risk club members with up to 94% confidence and explains which factors affect the risk score”.", "caveatRu": "Формулировка и цифра 94% взяты с сайта самого вендора; независимой проверки нет.", "caveatEn": "The wording and the 94% figure are taken from the vendor's own site; there is no independent verification.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "vinSUITE", "url": "https://www.vinsuite.com/vinsightanalytics" } ] }, { "id": 185, "catalogId": 189, "slug": "sogrape-185", "url": "https://vinumexmachina.com/casebook/cases/#case-185", "nameRu": "Sogrape", "nameEn": "Sogrape", "operatorRu": "Sogrape Vinhos", "operatorEn": "Sogrape Vinhos", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "business", "tech": "other", "stage": "commercial", "country": [ "pt" ], "confidence": "b", "aiKind": "yes", "techRu": "Пилоты ИИ плюс технологии водоочистки", "techEn": "AI pilots plus water-treatment technologies", "doesRu": "Программа устойчивости", "doesEn": "Sustainability programme", "resultsRu": "Португалия: выбросы −13,2%, водопотребление −40,5% (с 21,9 до 13 литров на бутылку 0,75)", "resultsEn": "Portugal: emissions −13.2%, water use −40.5% (from 21.9 to 13 litres per 0.75 bottle)", "caveatRu": "Источник не связывает эти показатели напрямую с ИИ-пилотами: он относит их к технологиям водоочистки.", "caveatEn": "The source does not link these figures directly to the AI pilots: it attributes them to water-treatment technologies.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Agroportal", "url": "https://www.agroportal.pt/sogrape-reduz-emissoes-de-gee-e-consumo-de-agua-em-2025/" } ] }, { "id": 186, "catalogId": 190, "slug": "chatgpt-protiv-ekzamena-master-sommelier-186", "url": "https://vinumexmachina.com/casebook/cases/#case-186", "nameRu": "ChatGPT против экзамена Master Sommelier", "nameEn": "ChatGPT versus the Master Sommelier exam", "operatorRu": "Независимый тест", "operatorEn": "Independent test", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "LLM", "techEn": "LLM", "doesRu": "Ответы на теоретические вопросы уровня Master Sommelier", "doesEn": "Answers theory questions at Master Sommelier level", "resultsRu": "Пройдены три теоретические секции экзамена (неофициальный тест).", "resultsEn": "Three theory sections of the exam were passed (unofficial test).", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "март 2023", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2023/03/chatgpt-just-passed-three-of-the-master-sommelier-theory-exams/" } ] }, { "id": 187, "catalogId": 191, "slug": "weinheimer-group-ai-marketing-readiness-report-187", "url": "https://vinumexmachina.com/casebook/cases/#case-187", "nameRu": "Weinheimer Group AI Marketing Readiness Report", "nameEn": "Weinheimer Group AI Marketing Readiness Report", "operatorRu": "Опрос виноделен", "operatorEn": "Survey of wineries", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "Оптимизация под ИИ-поиск (GEO)", "techEn": "Optimisation for AI search (GEO)", "doesRu": "Видимость винодельни в ответах ИИ-ассистентов", "doesEn": "Winery visibility in the answers of AI assistants", "resultsRu": "93% опрошенных виноделен экспериментируют с ИИ или собирают информацию; 7% не считают это приоритетом; 60% главной возможностью называют улучшение находимости; 36% главным барьером — неотличимость хайпа от реальности; 29% ждут доказательств ROI.", "resultsEn": "93% of the wineries surveyed are experimenting with AI or gathering information; 7% do not treat it as a priority; 60% name better findability as the main opportunity; 36% name the indistinguishability of hype from reality as the main barrier; 29% are waiting for proof of ROI.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "апрель 2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2026/04/ai-hype-or-reality-wine-sector-weighs-its-next-move/" } ] }, { "id": 188, "catalogId": 192, "slug": "weine-ai-188", "url": "https://vinumexmachina.com/casebook/cases/#case-188", "nameRu": "weine.ai", "nameEn": "weine.ai", "operatorRu": "importweine.de", "operatorEn": "importweine.de", "countryRu": "Германия", "countryEn": "Germany", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "de" ], "confidence": "c", "aiKind": "yes", "techRu": "LLM-поиск на естественном языке", "techEn": "Natural-language LLM search", "doesRu": "Подбор вина по описанию потребности", "doesEn": "Wine selection from a description of the need", "resultsRu": "По данным компании, 109 вин Мозеля и Саара, 106 рислингов; 6 подборок в неделю", "resultsEn": "According to the company, 109 Mosel and Saar wines, 106 Rieslings; 6 selections a week", "caveatRu": "Это живые счётчики каталога самой компании — значения меняются; независимой проверки нет.", "caveatEn": "These are live counters from the company's own catalogue — the values change; there is no independent verification.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "weine.ai", "url": "https://weine.ai/" } ] }, { "id": 189, "catalogId": 193, "slug": "familia-morcos-189", "url": "https://vinumexmachina.com/casebook/cases/#case-189", "nameRu": "Familia Morcos", "nameEn": "Familia Morcos", "operatorRu": "Familia Morcos", "operatorEn": "Familia Morcos", "countryRu": "Аргентина", "countryEn": "Argentina", "domain": "business", "tech": "llm", "stage": "pilot", "country": [ "ar" ], "confidence": "c", "aiKind": "yes", "techRu": "Генеративный ИИ для этикеток + внутренний LLM по энологии", "techEn": "Generative AI for labels + an internal LLM on oenology", "doesRu": "Дизайн этикетки и внутренняя база знаний", "doesEn": "Label design and an internal knowledge base", "resultsRu": "По заявлению компании, вино «на 100% спроектированное ИИ» ещё не выпущено.", "resultsEn": "According to the company's statement, a wine “100% designed by AI” has not yet been released.", "caveatRu": "Формулировка принадлежит самой компании; независимого подтверждения нет.", "caveatEn": "The wording is the company's own; there is no independent confirmation.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2025, "yearDisplay": "2023–2025", "yearRaw": "2023–2025", "sectionKey": "C", "sectionRu": "C. Винный бизнес", "sources": [ { "name": "Wines of Argentina", "url": "https://blog.winesofargentina.com/destacadas/artificial-intelligence-wine/" } ] }, { "id": 190, "catalogId": 194, "slug": "genomnaya-selektsiya-vinograda-s-ii-190", "url": "https://vinumexmachina.com/casebook/cases/#case-190", "nameRu": "Геномная селекция винограда с ИИ", "nameEn": "Grapevine genomic selection with AI", "operatorRu": "Институт агрогеномики в Шэньчжэне, Китайская академия сельхознаук (Чжоу Юнфэн)", "operatorEn": "Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences (Zhou Yongfeng)", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "breeding", "stage": "research", "country": [ "cn" ], "confidence": "a", "aiKind": "yes", "techRu": "ML-модель геномного отбора + пангеном Grapepan v1.0", "techEn": "Genomic selection ML model + the Grapepan v1.0 pangenome", "doesRu": "Предсказывает селекционный потенциал по геному, сокращая многолетние циклы скрещивания", "doesEn": "Predicts breeding potential from the genome, shortening multi-year crossing cycles", "resultsRu": "Точность предсказания 85%; данные по 400+ из ~10 000 сортов, 29 признаков; эффективность селекции выросла вчетверо; 6 китайских патентов.", "resultsEn": "Prediction accuracy 85%; data on 400+ of ~10,000 grape varieties, 29 traits; breeding efficiency rose fourfold; 6 Chinese patents.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024, Nature Genetics", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Xinhua", "url": "https://english.news.cn/20241104/6cffb4554f1e43098c4dc68577755711/c.html" } ] }, { "id": 191, "catalogId": 195, "slug": "genomnyy-otbor-na-ustoychivost-k-vreditelyam-191", "url": "https://vinumexmachina.com/casebook/cases/#case-191", "nameRu": "Геномный отбор на устойчивость к вредителям", "nameEn": "Genomic selection for pest resistance", "operatorRu": "Китайская академия тропического сельхоза, Институт плодоводства в Чжэнчжоу, Университет штата Вашингтон", "operatorEn": "Chinese Academy of Tropical Agriculture, Zhengzhou Fruit Research Institute, Washington State University", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "breeding", "stage": "research", "country": [ "cn" ], "confidence": "a", "aiKind": "yes", "techRu": "Глубокие свёрточные сети (VGG16, ResNet) + геномный отбор", "techEn": "Deep convolutional networks (VGG16, ResNet) + genomic selection", "doesRu": "Оценка повреждений по изображениям и геномное прогнозирование для винных и столовых сортов", "doesEn": "Damage assessment from images and genomic prediction for wine and table grape varieties", "resultsRu": "VGG16: точность классификации 95,3%; DCNN-PDS: R² = 0,88; геномный отбор 95,7% по бинарным признакам; выявлено 69 локусов и 139 генов-кандидатов.", "resultsEn": "VGG16: classification accuracy 95.3%; DCNN-PDS: R² = 0.88; genomic selection 95.7% on binary traits; 69 loci and 139 candidate genes identified.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025, Horticulture Research", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Oxford Academic", "url": "https://academic.oup.com/hr/article/12/8/uhaf128/8126322" } ] }, { "id": 192, "catalogId": 196, "slug": "ii-fenotipirovanie-i-klimaticheskaya-selektsiya-192", "url": "https://vinumexmachina.com/casebook/cases/#case-192", "nameRu": "ИИ-фенотипирование и климатическая селекция", "nameEn": "AI phenotyping and climate breeding", "operatorRu": "Китайская академия наук, опытный виноградник в Нинся (Дай Чжанъу, Се Цзюнь)", "operatorEn": "Chinese Academy of Sciences, experimental vineyard in Ningxia (Dai Zhanwu, Xie Jun)", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "breeding", "stage": "pilot", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "Распознавание изображений для оценки фенотипа + климатические модели", "techEn": "Image recognition for phenotype assessment + climate models", "doesRu": "Скрининг гибридов и моделирование пригодности виноградника на 10, 30 и 50 лет вперёд", "doesEn": "Screening hybrids and modelling vineyard suitability 10, 30 and 50 years ahead", "resultsRu": "~20 000 новых генотипов в год проходят скрининг.", "resultsEn": "~20,000 new genotypes a year are screened.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "AFP", "url": "https://www.legit.ng/business-economy/economy/1617283-china-wine-industry-breed-climate-resilience/" } ] }, { "id": 193, "catalogId": 197, "slug": "umnoe-oroshenie-i-iot-v-ninsya-193", "url": "https://vinumexmachina.com/casebook/cases/#case-193", "nameRu": "Умное орошение и IoT в Нинся", "nameEn": "Smart irrigation and IoT in Ningxia", "operatorRu": "Виноградная база GreatWall Terroir и винодельня Huangkou у восточного подножия Хэланьшань", "operatorEn": "GreatWall Terroir's grape planting base and Huangkou Winery, at the eastern foot of Helan Mountain", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "sensors-iot", "stage": "scaled", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "IoT-датчики почвы и погоды, управление поливом из приложения, цифровой контроль ферментации", "techEn": "IoT soil and weather sensors, irrigation control from an app, digital fermentation control", "doesRu": "Капельный полив по данным и управление брожением", "doesEn": "Data-driven drip irrigation and fermentation management", "resultsRu": "На виноградной базе GreatWall Terroir, где капельный полив с датчиками пришёл на смену поливу напуском, расход воды снижен с 700–800 до 220–260 м³ на му в год. Пять работников теперь обслуживают более 7 000 му вместо 300 — рост производительности более чем в двадцать раз.", "resultsEn": "At GreatWall Terroir's grape planting base, where drip irrigation with sensors replaced flood irrigation, water use was cut from 700–800 to 220–260 m³ per mu a year. Five workers now cover more than 7,000 mu instead of 300 — a more than twentyfold rise in productivity.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Xinhua", "url": "https://english.news.cn/20250613/2d789a4410be4e2baadc698dc6add599/c.html" } ] }, { "id": 194, "catalogId": 198, "slug": "xige-estate-194", "url": "https://vinumexmachina.com/casebook/cases/#case-194", "nameRu": "Xige Estate (西鸽酒庄)", "nameEn": "Xige Estate (西鸽酒庄)", "operatorRu": "Xige Estate", "operatorEn": "Xige Estate", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "IoT + собственная big-data платформа", "techEn": "IoT + an in-house big-data platform", "doesRu": "Первая китайская винодельня, полностью оцифровавшая управление виноградником", "doesEn": "The first Chinese winery to fully digitise vineyard management", "resultsRu": "34 млн записей данных, 59 интерфейсов данных, 43 000 обращений обслужено; программа «одна бутылка — один код» дала более 20 млн юаней онлайн-продаж, рост 70% за год, по 25 винодельням и 104 винам.", "resultsEn": "34m data records, 59 data interfaces, 43,000 enquiries handled; the “one bottle — one code” programme produced more than 20m yuan in online sales, up 70% in a year, across 25 wineries and 104 wines.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "China News", "url": "https://www.chinanews.com.cn/cj/2024/12-02/10329190.shtml" } ] }, { "id": 195, "catalogId": 199, "slug": "robot-monitoringa-vrediteley-khelanshan-195", "url": "https://vinumexmachina.com/casebook/cases/#case-195", "nameRu": "Робот мониторинга вредителей Хэланьшань", "nameEn": "Helan Mountain pest monitoring robot", "operatorRu": "Команда цифровизации винной отрасли Хэланьшань (Чжан Сюэцзянь)", "operatorEn": "Helan Mountain wine industry digitalisation team (Zhang Xuejian)", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "robotics", "stage": "pilot", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "Наземный робот с камерами + облачная аналитика", "techEn": "Ground robot with cameras + cloud analytics", "doesRu": "Раннее предупреждение о вредителях и болезнях", "doesEn": "Early warning of pests and diseases", "resultsRu": "Демонстрационная зона ~390 му; затраты на пестициды −25%, на труд −10%", "resultsEn": "Demonstration area ~390 mu; pesticide costs −25%, labour −10%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "КЧЖГ", "url": "https://www.kczg.org.cn/rules/detail?id=6316873" } ] }, { "id": 196, "catalogId": 200, "slug": "platforma-1-n-100-ninsya-196", "url": "https://vinumexmachina.com/casebook/cases/#case-196", "nameRu": "Платформа «1+N+100» Нинся", "nameEn": "Ningxia “1+N+100” platform", "operatorRu": "Правительство Нинся, Бюро развития винной отрасли", "operatorEn": "Government of Ningxia, Wine Industry Development Bureau", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "sensors-iot", "stage": "scaled", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "Централизованный отраслевой дата-центр + прикладные системы", "techEn": "Centralised industry data centre + application systems", "doesRu": "Единая инфраструктура: IoT-мониторинг, предупреждение о болезнях, управление водой и удобрениями", "doesEn": "A single infrastructure: IoT monitoring, disease warning, water and fertiliser management", "resultsRu": "Обслуживает 100 виноделен; 14 цифровых сервисных систем; создано 8 «цифровых виноделен».", "resultsEn": "Serves 100 wineries; 14 digital service systems; 8 “digital wineries” created.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "China News", "url": "https://www.chinanews.com.cn/cj/2024/12-02/10329190.shtml" } ] }, { "id": 197, "catalogId": 201, "slug": "sputnikovo-dronovaya-set-ninsya-nunken-197", "url": "https://vinumexmachina.com/casebook/cases/#case-197", "nameRu": "Спутниково-дроновая сеть Нинся Нунькэнь", "nameEn": "Ningxia Nongken satellite and drone network", "operatorRu": "Государственная агрокорпорация Нинся Нунькэнь", "operatorEn": "Ningxia Nongken state agricultural corporation", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "Спутниковое зондирование + дроны", "techEn": "Satellite sensing + drones", "doesRu": "Снижение ущерба от погодных явлений, данные поступают в региональную платформу", "doesEn": "Reducing damage from weather events; the data feeds the regional platform", "resultsRu": "606 000 му виноградников и 136 виноделен — показатели региональной платформы всего восточного подножия Хэланьшань, а не корпорации Нинся Нунькэнь", "resultsEn": "606,000 mu of vineyards and 136 wineries — figures for the regional platform of the whole eastern foot of Helan Mountain, not for the Ningxia Nongken corporation", "caveatRu": "Цифры относятся к региональной платформе восточного подножия Хэланьшань, а не к самой корпорации.", "caveatEn": "The figures relate to the regional platform of the eastern foot of Helan Mountain, not to the corporation itself.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "China News", "url": "https://www.chinanews.com.cn/cj/2026/05-08/10617345.shtml" } ] }, { "id": 198, "catalogId": 202, "slug": "bolshaya-model-vyrashchivaniya-vinograda-i-198", "url": "https://vinumexmachina.com/casebook/cases/#case-198", "nameRu": "«Большая модель выращивания винограда и виноделия Лайшань»", "nameEn": "“Laishan grape growing and winemaking large model”", "operatorRu": "Inspur Cloud + вычислительный центр Китайского сельхозуниверситета + компания в Яньтае", "operatorEn": "Inspur Cloud + the computing centre of China Agricultural University + a company in Yantai", "countryRu": "Китай", "countryEn": "China", "domain": "viticulture", "tech": "llm", "stage": "pilot", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "Фундаментальная ИИ-модель", "techEn": "AI foundation model", "doesRu": "Протоколы климатической адаптации, точное внесение воды и удобрений, прогноз болезней; ИИ-симуляция ферментации и выдержки с динамической оптимизацией параметров и оценкой профиля", "doesEn": "Climate adaptation protocols, precise water and fertiliser application, disease forecasting; AI simulation of fermentation and ageing with dynamic parameter optimisation and profile assessment", "resultsRu": "Количественных KPI не раскрыто.", "resultsEn": "No quantitative KPIs disclosed.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Правительство Яньтая", "url": "https://nongye.yantai.gov.cn/col/col20529/art/2026/art_27b95eced62e44dc92070dbefde74b14.html" } ] }, { "id": 199, "catalogId": 203, "slug": "tsifrovaya-transformatsiya-changyu-199", "url": "https://vinumexmachina.com/casebook/cases/#case-199", "nameRu": "Цифровая трансформация Changyu", "nameEn": "Changyu digital transformation", "operatorRu": "Changyu (Яньтай)", "operatorEn": "Changyu (Yantai)", "countryRu": "Китай", "countryEn": "China", "domain": "winemaking", "tech": "sensors-iot", "stage": "scaled", "country": [ "cn" ], "confidence": "b", "aiKind": "yes", "techRu": "Блокчейн-прослеживаемость, платформа клиентских данных, «безлюдный» цех", "techEn": "Blockchain traceability, a customer data platform, an “unmanned” workshop", "doesRu": "Прослеживаемость, управление лояльностью, ферментация под управлением планшетов", "doesEn": "Traceability, loyalty management, tablet-controlled fermentation", "resultsRu": "Более 200 млн бутылок в блокчейне к 2023; 19 линий, 140 ёмкостей под планшетным управлением; 2,8 млн участников программы лояльности; экономия ~20 млн юаней в год на борьбе с подделками; выручка 2023 +11,89%, чистая прибыль +24,2%", "resultsEn": "More than 200m bottles on the blockchain by 2023; 19 lines, 140 tanks under tablet control; 2.8m loyalty programme members; ~20m yuan a year saved on countering counterfeits; 2023 revenue +11.89%, net profit +24.2%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2012, "yearEnd": 2024, "yearDisplay": "2012–2024", "yearRaw": "2012–2024", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Шуйму", "url": "https://u.shm.com.cn/2024-04/17/content_5409947.html" } ] }, { "id": 200, "catalogId": 204, "slug": "alibaba-novaya-roznitsa-v-vine-200", "url": "https://vinumexmachina.com/casebook/cases/#case-200", "nameRu": "Alibaba «новая розница» в вине", "nameEn": "Alibaba “new retail” in wine", "operatorRu": "Hema, флагманы Tmall, Future Bar", "operatorEn": "Hema, Tmall flagships, Future Bar", "countryRu": "Китай", "countryEn": "China", "domain": "business", "tech": "cv", "stage": "pilot", "country": [ "cn" ], "confidence": "c", "aiKind": "yes", "techRu": "RFID-распознавание полки, распознавание лиц на кассе, робот-хостес, умный QR-холодильник", "techEn": "RFID shelf recognition, face recognition at the checkout, a hostess robot, a smart QR fridge", "doesRu": "Витрина безлюдной винной розницы", "doesEn": "A showcase of unmanned wine retail", "resultsRu": "Пилоты в Шанхае и Ханчжоу, масштаб не раскрыт.", "resultsEn": "Pilots in Shanghai and Hangzhou; scale not disclosed.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2018, "yearDisplay": "2018", "yearRaw": "2018", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Alizila", "url": "https://www.alizila.com/china-wine-new-retail/" } ] }, { "id": 201, "catalogId": 205, "slug": "fujitsu-okunota-winery-201", "url": "https://vinumexmachina.com/casebook/cases/#case-201", "nameRu": "Fujitsu + Okunota Winery", "nameEn": "Fujitsu + Okunota Winery", "operatorRu": "Okunota Winery", "operatorEn": "Okunota Winery", "countryRu": "Япония", "countryEn": "Japan", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "jp" ], "confidence": "b", "aiKind": "yes", "techRu": "Сеть датчиков (температура, осадки, влажность) с интервалом 10 минут + агрооблако", "techEn": "Sensor network (temperature, rainfall, humidity) at 10-minute intervals + an agriculture cloud", "doesRu": "Анализ микроклимата для сокращения обработок", "doesEn": "Microclimate analysis to reduce treatments", "resultsRu": "Работает с июня 2011 года. Четырёхлетний анализ выявил пороги риска плесени, что позволило сократить частоту обработок; вино вошло в национальный список Wonder 500.", "resultsEn": "Running since June 2011. A four-year analysis identified mould risk thresholds, which made it possible to reduce the frequency of treatments; the wine entered the national Wonder 500 list.", "caveatRu": "Опыт описан только для одной винодельни; масштабирование источником не подтверждается.", "caveatEn": "The experience is described for one winery only; scaling is not confirmed by the source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2011, "yearEnd": null, "yearDisplay": "2011–", "yearRaw": "2011–", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Fujitsu", "url": "https://www.fujitsu.com/global/about/environment/activities/japan/winefarm/" } ] }, { "id": 202, "catalogId": 206, "slug": "prognoz-vspyshek-mildyu-yamanasi-202", "url": "https://vinumexmachina.com/casebook/cases/#case-202", "nameRu": "Прогноз вспышек милдью, Яманаси", "nameEn": "Downy mildew outbreak forecasting, Yamanashi", "operatorRu": "Консорциум Центра винных наук Университета Яманаси (Судзуки Сюндзи)", "operatorEn": "Consortium of the Wine Science Centre of the University of Yamanashi (Suzuki Shunji)", "countryRu": "Япония", "countryEn": "Japan", "domain": "viticulture", "tech": "disease-weather", "stage": "pilot", "country": [ "jp" ], "confidence": "b", "aiKind": "yes", "techRu": "Датчики + облачная модель прогноза + мобильные оповещения", "techEn": "Sensors + a cloud forecasting model + mobile alerts", "doesRu": "Раннее вмешательство для органического виноградарства с минимумом обработок", "doesEn": "Early intervention for organic viticulture with a minimum of treatments", "resultsRu": "Результатов пока нет.", "resultsEn": "No results yet.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Vino Joy", "url": "https://vino-joy.com/2022/09/07/japans-largest-wine-region-uses-ai-for-organic-viticulture/" } ] }, { "id": 203, "catalogId": 207, "slug": "demonstratsionnyy-proekt-umnogo-vinogradarstva-203", "url": "https://vinumexmachina.com/casebook/cases/#case-203", "nameRu": "Демонстрационный проект умного виноградарства", "nameEn": "Smart viticulture demonstration project", "operatorRu": "Suntory Wine International, Japan Premium Vineyard, Nippon Steel Solutions", "operatorEn": "Suntory Wine International, Japan Premium Vineyard, Nippon Steel Solutions", "countryRu": "Япония", "countryEn": "Japan", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "jp" ], "confidence": "b", "aiKind": "yes", "techRu": "Контроль корневой зоны + роботизированная поддержка работ + ИИ-анализ изображений урожая", "techEn": "Root zone control + robotic support for operations + AI image analysis of the harvest", "doesRu": "Совмещение японской длиннорукавной формировки и европейской шпалеры", "doesEn": "Combining Japanese long-arm training and European trellising", "resultsRu": "4 га виноградника JPV (сорт кошу), 3 га в первой фазе; поддержка Минсельхоза Японии", "resultsEn": "4 ha of JPV vineyard (Koshu variety), 3 ha in the first phase; support from Japan's Ministry of Agriculture", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2019, "yearDisplay": "2019", "yearRaw": "2019", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Diamond", "url": "https://diamond.jp/articles/-/215297" } ] }, { "id": 204, "catalogId": 208, "slug": "obuchenie-vinogradarstvu-cherez-5g-i-umnye-ochki-204", "url": "https://vinumexmachina.com/casebook/cases/#case-204", "nameRu": "Обучение виноградарству через 5G и умные очки", "nameEn": "Viticulture training via 5G and smart glasses", "operatorRu": "Программа префектуры Яманаси (столовый виноград)", "operatorEn": "Yamanashi Prefecture programme (table grapes)", "countryRu": "Япония", "countryEn": "Japan", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "jp" ], "confidence": "b", "aiKind": "yes", "techRu": "Умные очки + локальная сеть 5G + ИИ", "techEn": "Smart glasses + a local 5G network + AI", "doesRu": "Передача техники опытного фермера новичкам с ИИ-поддержкой", "doesEn": "Passing an experienced farmer's technique to novices with AI support", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "≈2021", "yearRaw": "~2021", "sectionKey": "G1", "sectionRu": "G1. Китай, Япония, Корея", "sources": [ { "name": "Префектура Яманаси", "url": "https://www.pref.yamanashi.jp/try_yamanashi/testbed_yuchi/jirei/smartagri.html" } ] }, { "id": 205, "catalogId": 209, "slug": "grapevine-205", "url": "https://vinumexmachina.com/casebook/cases/#case-205", "nameRu": "GRAPEVINE", "nameEn": "GRAPEVINE", "operatorRu": "Университет Аристотеля в Салониках, ITAINNOVA, CESGA, Университет Сарагосы, Atos", "operatorEn": "Aristotle University of Thessaloniki, ITAINNOVA, CESGA, University of Zaragoza, Atos", "countryRu": "Испания, Греция", "countryEn": "Spain, Greece", "domain": "viticulture", "tech": "disease-weather", "stage": "research", "country": [ "es", "gr" ], "confidence": "a", "aiKind": "yes", "techRu": "ML на суперкомпьютерах", "techEn": "ML on supercomputers", "doesRu": "Прогноз вспышек милдью; пилоты в PDO Гуменисса (Греция) и Арагоне (Испания)", "doesEn": "Downy mildew outbreak forecasting; pilots in PDO Goumenissa (Greece) and Aragon (Spain)", "resultsRu": "Бюджет €2 481 670, 75% софинансирования ЕС", "resultsEn": "Budget €2,481,670, 75% EU co-funding", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2022, "yearDisplay": "2019–2022", "yearRaw": "2019–2022", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "ITA", "url": "https://www.ita.es/en/project/grapevine/" } ] }, { "id": 206, "catalogId": 210, "slug": "bacchus-206", "url": "https://vinumexmachina.com/casebook/cases/#case-206", "nameRu": "BACCHUS", "nameEn": "BACCHUS", "operatorRu": "Университет Аристотеля в Салониках (координатор)", "operatorEn": "Aristotle University of Thessaloniki (coordinator)", "countryRu": "Греция", "countryEn": "Greece", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "gr" ], "confidence": "a", "aiKind": "yes", "techRu": "Компьютерное зрение, гиперспектральная съёмка, ИИ-принятие решений", "techEn": "Computer vision, hyperspectral imaging, AI decision-making", "doesRu": "Два кооперирующихся робота с адаптивными захватами оценивают зрелость и выборочно собирают виноград", "doesEn": "Two cooperating robots with adaptive grippers assess ripeness and selectively harvest grapes", "resultsRu": "Бюджет €5 104 943, Horizon 2020; испытан на нескольких сортах.", "resultsEn": "Budget €5,104,943, Horizon 2020; tested on several grape varieties.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2023, "yearDisplay": "2020–2023", "yearRaw": "2020–2023", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "CORDIS", "url": "https://cordis.europa.eu/project/id/871704" } ] }, { "id": 207, "catalogId": 211, "slug": "programma-nmr-autentifikatsii-vengerskikh-vin-207", "url": "https://vinumexmachina.com/casebook/cases/#case-207", "nameRu": "Программа NMR-аутентификации венгерских вин", "nameEn": "NMR authentication programme for Hungarian wines", "operatorRu": "Министерство сельского хозяйства Венгрии, Bruker, Diagnosticum", "operatorEn": "Hungarian Ministry of Agriculture, Bruker, Diagnosticum", "countryRu": "Венгрия", "countryEn": "Hungary", "domain": "winemaking", "tech": "chemometrics", "stage": "commercial", "country": [ "hu" ], "confidence": "b", "aiKind": "yes", "techRu": "ЯМР + хемометрический фингерпринтинг", "techEn": "NMR + chemometric fingerprinting", "doesRu": "Референсная база венгерских вин, включая токайские, для проверки происхождения, сорта и винтажа", "doesEn": "A reference database of Hungarian wines, including Tokaj wines, for verifying origin, grape variety and vintage", "resultsRu": "Двухлетнее окно сбора образцов; присоединяется к базам по Испании, Италии, Франции, Чили, Австрии, Германии.", "resultsEn": "A two-year sample collection window; joins the databases for Spain, Italy, France, Chile, Austria and Germany.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2017, "yearDisplay": "2017", "yearRaw": "2017", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "PR Newswire", "url": "https://www.prnewswire.com/news-releases/hungarian-ministry-of-agriculture-selects-bruker-nmr-foodscreener-for-authentication-and-identification-of-hungarian-wines-300501043.html" } ] }, { "id": 208, "catalogId": 212, "slug": "uav-ml-zonirovanie-vinogradnika-208", "url": "https://vinumexmachina.com/casebook/cases/#case-208", "nameRu": "UAV + ML зонирование виноградника", "nameEn": "UAV + ML vineyard zoning", "operatorRu": "Университет Нови-Сада, Сремски-Карловци, Фрушка-Гора", "operatorEn": "University of Novi Sad, Sremski Karlovci, Fruška Gora", "countryRu": "Сербия", "countryEn": "Serbia", "domain": "viticulture", "tech": "remote-sensing", "stage": "research", "country": [ "rs" ], "confidence": "a", "aiKind": "yes", "techRu": "YOLO для детекции лоз + k-means для зонирования, NDVI и NPK", "techEn": "YOLO for vine detection + k-means for zoning, NDVI and NPK", "doesRu": "Автоматическое определение рядов и границ зон управления по мультиспектральной съёмке", "doesEn": "Automatic detection of rows and management zone boundaries from multispectral imagery", "resultsRu": "Точность детекции лоз 90%; исследования 2020 и 2022 годов", "resultsEn": "Vine detection accuracy 90%; studies from 2020 and 2022", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "Remote Sensing", "url": "https://www.mdpi.com/2072-4292/16/3/584" } ] }, { "id": 209, "catalogId": 213, "slug": "tsifrovoy-vinogradnik-sevastopol-209", "url": "https://vinumexmachina.com/casebook/cases/#case-209", "nameRu": "«Цифровой виноградник» (Севастополь)", "nameEn": "“Digital vineyard” (Sevastopol)", "operatorRu": "Севастопольский госуниверситет, Крымский федеральный университет, институт «Магарач», винодельня «Коктебель»", "operatorEn": "Sevastopol State University, Crimean Federal University, the Magarach institute, the Koktebel winery", "countryRu": "Россия (Крым)", "countryEn": "Russia (Crimea)", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "ru" ], "confidence": "c", "aiKind": "yes", "techRu": "Датчики почвы, растения и воздуха, дроновый мониторинг вредителей, планируемый ИИ-распознаватель болезней", "techEn": "Soil, plant and air sensors, drone pest monitoring, a planned AI disease recogniser", "doesRu": "Умный виноградник с «цифровым помощником агронома»", "doesEn": "A smart vineyard with a “digital agronomist's assistant”", "resultsRu": "2,5 га по плану, 2 га пересажено, более 5 000 саженцев, 8 сортов; установка датчиков была запланирована на март 2023. Модуль ИИ-распознавания болезней на момент публикации оставался в планах.", "resultsEn": "2.5 ha planned, 2 ha replanted, more than 5,000 vines, 8 grape varieties; sensor installation was scheduled for March 2023. The AI disease recognition module was still at the planning stage at the time of publication.", "caveatRu": "На момент публикации источника датчики были только запланированы, а ИИ-распознавание болезней — в планах.", "caveatEn": "At the time the source was published the sensors were only planned, and AI disease recognition was at the planning stage.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": 2023, "yearDisplay": "2021–2023", "yearRaw": "2021–2023", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "РИА Новости Крым", "url": "https://crimea.ria.ru/20230206/tsifrovye-vinogradniki-chto-eto-takoe-i-zachem-oni-rossii-1126708200.html" } ] }, { "id": 210, "catalogId": 214, "slug": "natsionalnyy-kadastr-vinogradnikov-210", "url": "https://vinumexmachina.com/casebook/cases/#case-210", "nameRu": "Национальный кадастр виноградников", "nameEn": "National vineyard cadastre", "operatorRu": "Национальное агентство вина Грузии", "operatorEn": "National Wine Agency of Georgia", "countryRu": "Грузия", "countryEn": "Georgia", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "ge" ], "confidence": "b", "aiKind": "adjacent", "techRu": "Дроновая ортофотосъёмка + ГИС (ИИ не подтверждён)", "techEn": "Drone orthophotography + GIS (AI not confirmed)", "doesRu": "Кадастровое картирование виноградников", "doesEn": "Cadastral mapping of vineyards", "resultsRu": "Развёртывание с 2014 до полного покрытия Кахетии; около 20 000 виноградарей зарегистрировано к 2021.", "resultsEn": "Rolled out from 2014 to full coverage of Kakheti; about 20,000 grape growers registered by 2021.", "caveatRu": "", "caveatEn": "", "whyRu": "Ортофотосъёмка и ГИС без распознавания. Инфраструктура данных.", "whyEn": "Orthophotography and GIS without recognition. Data infrastructure.", "dataRu": "", "dataEn": "", "yearStart": 2014, "yearEnd": 2021, "yearDisplay": "2014–2021", "yearRaw": "2014–2021", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "MEPA Georgia", "url": "https://www.mepa.gov.ge/En/News/Details/20443" } ] }, { "id": 211, "catalogId": 215, "slug": "blokcheyn-proslezhivaemost-na-cardano-211", "url": "https://vinumexmachina.com/casebook/cases/#case-211", "nameRu": "Блокчейн-прослеживаемость на Cardano", "nameEn": "Blockchain traceability on Cardano", "operatorRu": "Фонд Cardano, Национальное агентство вина, Ассоциация виноделов Болниси, Scantrust", "operatorEn": "Cardano Foundation, National Wine Agency, Bolnisi Winemakers Association, Scantrust", "countryRu": "Грузия", "countryEn": "Georgia", "domain": "business", "tech": "other", "stage": "pilot", "country": [ "ge" ], "confidence": "b", "aiKind": "adjacent", "techRu": "Блокчейн + QR (не ИИ)", "techEn": "Blockchain + QR (not AI)", "doesRu": "Пилот защиты происхождения", "doesEn": "Origin-protection pilot", "resultsRu": "До 100 000 бутылок урожая 2022; ассоциация Болниси производит ~200 000 бутылок в год с целью 12 млн за 10 лет.", "resultsEn": "Up to 100,000 bottles of the 2022 harvest; the Bolnisi association produces ~200,000 bottles a year, with a target of 12m over 10 years.", "caveatRu": "", "caveatEn": "", "whyRu": "Блокчейн и QR-коды. Смежная технология прослеживаемости.", "whyEn": "Blockchain and QR codes. Adjacent traceability technology.", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2023, "yearDisplay": "2022–2023", "yearRaw": "2022–2023", "sectionKey": "G2", "sectionRu": "G2. Восточная Европа, Кавказ, Греция, Россия", "sources": [ { "name": "Cardano Foundation", "url": "https://cardanofoundation.org/blog/cardano-foundation-partners-with-georgian-national-wine-agency" } ] }, { "id": 212, "catalogId": 216, "slug": "domaine-aubert-mathieu-212", "url": "https://vinumexmachina.com/casebook/cases/#case-212", "nameRu": "Domaine Aubert & Mathieu", "nameEn": "Domaine Aubert & Mathieu", "operatorRu": "OpenAI ChatGPT", "operatorEn": "OpenAI ChatGPT", "countryRu": "Франция (Лангедок)", "countryEn": "France (Languedoc)", "domain": "winemaking", "tech": "llm", "stage": "pilot", "country": [ "fr" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ChatGPT определил купаж (органические сира и гренаш), название вина «The End», форму бутылки и предложил цену, которую хозяйство скорректировало", "doesEn": "ChatGPT determined the blend (organic Syrah and Grenache), the wine's name “The End”, the bottle shape and suggested a price, which the estate adjusted", "resultsRu": "Цена: по Vitisphere «в районе двадцати евро», тираж 600 бутылок. Первое вино, публично приписанное авторству ИИ.", "resultsEn": "Price: according to Vitisphere “around twenty euros”; a run of 600 bottles. The first wine publicly attributed to AI authorship.", "caveatRu": "Цена приводится по Vitisphere; заявленные €29,90 подтвердить не удалось, первый источник недоступен.", "caveatEn": "The price is given according to Vitisphere; the claimed €29.90 could not be confirmed, and the first source is unavailable.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G3", "sectionRu": "G3. Внутренние программы производителей", "sources": [ { "name": "Wine-Searcher", "url": "https://www.wine-searcher.com/m/2023/04/introducing-the-first-ai-wine" }, { "name": "Vitisphere", "url": "https://www.vitisphere.com/actualite-99072-premier-vin-signe-par-lintelligence-artificielle-chatgpt.html" } ] }, { "id": 213, "catalogId": 217, "slug": "moet-hennessy-divine-213", "url": "https://vinumexmachina.com/casebook/cases/#case-213", "nameRu": "Moët Hennessy «Divine»", "nameEn": "Moët Hennessy “Divine”", "operatorRu": "OpenAI GPT-4", "operatorEn": "OpenAI GPT-4", "countryRu": "Франция", "countryEn": "France", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "fr" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Интерактивная ИИ-сомелье, обученная на экспертизе всех хозяйств группы, представленная как «оживающая картина»", "doesEn": "An interactive AI sommelier trained on the expertise of all the group's estates, presented as a “painting that comes to life”", "resultsRu": "Запуск летом 2024, планируется вывод в магазины и онлайн.", "resultsEn": "Launched in summer 2024; a rollout to shops and online is planned.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G3", "sectionRu": "G3. Внутренние программы производителей", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2024/10/five-ways-ai-is-impacting-the-wine-trade/" } ] }, { "id": 214, "catalogId": 218, "slug": "konsortsium-doca-rioja-214", "url": "https://vinumexmachina.com/casebook/cases/#case-214", "nameRu": "Консорциум DOCa Rioja", "nameEn": "DOCa Rioja consortium", "operatorRu": "Разработано советом наименования", "operatorEn": "Developed by the appellation council", "countryRu": "Испания", "countryEn": "Spain", "domain": "viticulture", "tech": "yield", "stage": "commercial", "country": [ "es" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Региональная ML-модель прогноза урожая по участкам", "doesEn": "Regional ML model for yield forecasting by plot", "resultsRu": "Точность до 96% на участках с детальными полевыми данными, более 91% в целом в 2024; покрытие около 66 000 га", "resultsEn": "Accuracy of up to 96% on plots with detailed field data, over 91% overall in 2024; coverage about 66,000 ha", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2025, "yearDisplay": "2022–2025", "yearRaw": "2022–2025", "sectionKey": "G3", "sectionRu": "G3. Внутренние программы производителей", "sources": [ { "name": "Vinetur", "url": "https://www.vinetur.com/20260804105214/riojas-ai-harvest-model-reached-96-accuracy-in-vineyards-with-detailed-field-data.html" } ] }, { "id": 215, "catalogId": 219, "slug": "marchesi-frescobaldi-215", "url": "https://vinumexmachina.com/casebook/cases/#case-215", "nameRu": "Marchesi Frescobaldi", "nameEn": "Marchesi Frescobaldi", "operatorRu": "AQuest (партнёр Ogilvy)", "operatorEn": "AQuest (Ogilvy partner)", "countryRu": "Италия", "countryEn": "Italy", "domain": "business", "tech": "cv", "stage": "commercial", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ML распознаёт этикетку и открывает AR-контент об истории хозяйства, терруаре и виноделии", "doesEn": "ML recognises the label and opens AR content about the estate's history, terroir and winemaking", "resultsRu": "Более 50 оцифрованных этикеток", "resultsEn": "More than 50 digitised labels", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2024, "yearDisplay": "2019–2024", "yearRaw": "2019, развитие 2024", "sectionKey": "G3", "sectionRu": "G3. 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Рецензируемые исследования", "sources": [ { "name": "Journal of Agricultural Science", "url": "https://doi.org/10.1017/S0021859624000145" } ] }, { "id": 230, "catalogId": 235, "slug": "nasiri-a-i-soavtory-230", "url": "https://vinumexmachina.com/casebook/cases/#case-230", "nameRu": "Nasiri A. и соавторы", "nameEn": "Nasiri A. and co-authors", "operatorRu": "", "operatorEn": "", "countryRu": "Иран", "countryEn": "Iran", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "ir" ], "confidence": "unstated", "aiKind": "yes", "techRu": "Модифицированный VGG16", "techEn": "Modified VGG16", "doesRu": "Определение сорта по листу", "doesEn": "Grape variety identification from the leaf", "resultsRu": "Средняя точность выше 99% при пятикратной кросс-валидации", "resultsEn": "Mean accuracy above 99% under five-fold cross-validation", "caveatRu": "Первый автор аффилирован с Университетом Теннесси (США); Иран — аффилиация соавторов и предмет исследования.", "caveatEn": "The first author is affiliated with the University of Tennessee (United States); Iran is the co-authors' affiliation and the subject of the study.", "whyRu": "", "whyEn": "", "dataRu": "не указан", "dataEn": "not stated", "yearStart": 2021, "yearEnd": 2021, "yearDisplay": "2021", "yearRaw": "2021", "sectionKey": "G4", "sectionRu": "G4. 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Рецензируемые исследования", "sources": [ { "name": "Plant Methods", "url": "https://doi.org/10.1186/s13007-020-00685-3" } ] }, { "id": 232, "catalogId": 237, "slug": "sawyer-e-fresno-state-cornell-uc-anr-232", "url": "https://vinumexmachina.com/casebook/cases/#case-232", "nameRu": "Sawyer E., Fresno State / Cornell / UC ANR", "nameEn": "Sawyer E., Fresno State / Cornell / UC ANR", "operatorRu": "", "operatorEn": "", "countryRu": "США", "countryEn": "United States", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "us" ], "confidence": "unstated", "aiKind": "yes", "techRu": "Гиперспектральная съёмка + Random Forest и 3D-CNN", "techEn": "Hyperspectral imaging + Random Forest and 3D-CNN", "doesRu": "Детекция вирусов красной пятнистости и лифролла", "doesEn": "Detection of red blotch and leafroll viruses", "resultsRu": "Бинарная классификация: на симптомном наборе CNN 87%, RF 82,4%; на досимптомном наборе RF 82,8%. Четыре класса: 77,7% и 76,9%. 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Сегментация: точность 0,97, полнота 0,81, F1 0,88.", "resultsEn": "Detection: precision up to 0.96 on Sangiovese, but recall only 0.59. Segmentation: precision 0.97, recall 0.81, F1 0.88.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "1 215 и 119 изображений, несколько виноградников и лет", "dataEn": "1,215 and 119 images, several vineyards and years", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G4", "sectionRu": "G4. 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Эталон — панель из 9–11 обученных дегустаторов.", "resultsEn": "Only 5 of 22 sensory descriptors reached R² above 0.7 (the best being green flavour, 0.881); 15 of 22 above 0.5. The reference is a panel of 9–11 trained tasters.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "74 образца, 3 винтажа, 8 регионов Южной Австралии", "dataEn": "74 samples, 3 vintages, 8 regions of South Australia", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G4", "sectionRu": "G4. 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Рецензируемые исследования", "sources": [ { "name": "Plants", "url": "https://doi.org/10.3390/plants13010135" } ] }, { "id": 242, "catalogId": 248, "slug": "prasad-k-v-universitet-vidzhayanagara-242", "url": "https://vinumexmachina.com/casebook/cases/#case-242", "nameRu": "Prasad K.V., Университет Виджаянагара", "nameEn": "Prasad K.V., Vijayanagara University", "operatorRu": "", "operatorEn": "", "countryRu": "Индия", "countryEn": "India", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "in" ], "confidence": "unstated", "aiKind": "yes", "techRu": "Глубокая CNN на базе VGG16", "techEn": "Deep CNN based on VGG16", "doesRu": "Классификация болезней листа", "doesEn": "Leaf disease classification", "resultsRu": "Точность на тесте 99,06%", "resultsEn": "Test accuracy 99.06%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "9 027 изображений из Kaggle", "dataEn": "9,027 images from Kaggle", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G4", "sectionRu": "G4. Рецензируемые исследования", "sources": [ { "name": "Scientific Reports", "url": "https://doi.org/10.1038/s41598-024-59562-x" } ] }, { "id": 243, "catalogId": 249, "slug": "benchmarki-detektsii-i-segmentatsii-grozdi-243", "url": "https://vinumexmachina.com/casebook/cases/#case-243", "nameRu": "Бенчмарки детекции и сегментации грозди", "nameEn": "Grape bunch detection and segmentation benchmarks", "operatorRu": "", "operatorEn": "", "countryRu": "Австралия, Китай", "countryEn": "Australia, China", "domain": "viticulture", "tech": "cv", "stage": "research", "country": [ "au", "cn" ], "confidence": "unstated", "aiKind": "yes", "techRu": "Mask R-CNN, PSPNet, DeepLabV3+", "techEn": "Mask R-CNN, PSPNet, DeepLabV3+", "doesRu": "Детекция соцветий и сегментация гроздей", "doesEn": "Inflorescence detection and bunch segmentation", "resultsRu": "Mask R-CNN по соцветиям шардоне: F1 98%, MAPE 6,92%; PSPNet сегментация гроздей IoU 87,42%; DeepLabV3+ IoU 88,44% при 60 мс на изображение", "resultsEn": "Mask R-CNN on Chardonnay inflorescences: F1 98%, MAPE 6.92%; PSPNet bunch segmentation IoU 87.42%; DeepLabV3+ IoU 88.44% at 60 ms per image", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "G4", "sectionRu": "G4. Рецензируемые исследования", "sources": [ { "name": "Agriculture", "url": "https://www.mdpi.com/2073-4395/12/10/2463" } ] }, { "id": 244, "catalogId": 250, "slug": "sommbench-244", "url": "https://vinumexmachina.com/casebook/cases/#case-244", "nameRu": "SommBench", "nameEn": "SommBench", "operatorRu": "Академический консорциум", "operatorEn": "Academic consortium", "countryRu": "Словакия", "countryEn": "Slovakia", "domain": "business", "tech": "llm", "stage": "research", "country": [ "sk" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Мультиязычный бенчмарк знаний о вине: теория, дополнение характеристик, сочетания с едой, на восьми языках; протестировано 18 моделей", "doesEn": "Multilingual benchmark of wine knowledge: theory, attribute completion, food pairing, in eight languages; 18 models tested", "resultsRu": "Точность по теории до 0,97 у лучших моделей; дополнение характеристик — потолок 0,63; сочетания с едой — лучший MCC всего 0,39; одна модель одобряла 86% предложенных пар независимо от их корректности. Перекличка с разрывом OenoBench — это редакторское сопоставление каталога: сам OenoBench в статье не упоминается.", "resultsEn": "Theory accuracy up to 0.97 for the best models; attribute completion has a ceiling of 0.63; food pairing — the best MCC is only 0.39; one model approved 86% of the pairings offered, regardless of whether they were correct. The parallel with the OenoBench gap is an editorial comparison made by this catalogue: OenoBench itself is not mentioned in the paper.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "arXiv", "url": "https://arxiv.org/html/2603.12117v1" } ] }, { "id": 245, "catalogId": 251, "slug": "wine-access-randomizirovannye-ispytaniya-llm-v-245", "url": "https://vinumexmachina.com/casebook/cases/#case-245", "nameRu": "Wine Access: рандомизированные испытания LLM в email-маркетинге", "nameEn": "Wine Access: randomised LLM trials in email marketing", "operatorRu": "Wine Access (DTC-ретейлер)", "operatorEn": "Wine Access (DTC retailer)", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Три рандомизированных контролируемых испытания: письма от людей против сгенерированных LLM против гибридных, около 9 000 клиентов в ячейке", "doesEn": "Three randomised controlled trials: human-written emails against LLM-generated against hybrid, about 9,000 customers per cell", "resultsRu": "LLM и гибрид сравнялись с людьми или обошли их по прибыли в двух испытаниях из трёх, до +9,36%. Копирайтеры стоили $375 000 в год, лицензии LLM — $1 000–1 200, гибрид — $63 500–94 950. Все варианты с ИИ примерно удвоили вероятность покупки против отсутствия письма.", "resultsEn": "LLM and hybrid matched or beat humans on profit in two trials out of three, by up to +9.36%. Copywriters cost $375,000 a year, LLM licences $1,000–1,200, hybrid $63,500–94,950. All the AI variants roughly doubled the probability of purchase against no email at all.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Quantitative Marketing and Economics", "url": "https://link.springer.com/article/10.1007/s11129-025-09303-9" } ] }, { "id": 246, "catalogId": 253, "slug": "amic-interpretiruemaya-model-vinnykh-retsenziy-246", "url": "https://vinumexmachina.com/casebook/cases/#case-246", "nameRu": "AMIC — интерпретируемая модель винных рецензий", "nameEn": "AMIC — interpretable model of wine reviews", "operatorRu": "Южный методистский университет (Цзин Цао)", "operatorEn": "Southern Methodist University (Jing Cao)", "countryRu": "США", "countryEn": "United States", "domain": "winemaking", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Предсказывает оценку по химическим параметрам и объясняет, какие именно слова рецензии двигают рейтинг", "doesEn": "Predicts the score from chemical parameters and explains which words of the review move the rating", "resultsRu": "Точность 89,26% при полной интерпретируемости. Слова «stained» и «carpet» оказались положительными предикторами, «quick» и «breezy» — отрицательными.", "resultsEn": "Accuracy 89.26% with full interpretability. The words “stained” and “carpet” turned out to be positive predictors, “quick” and “breezy” negative.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "SMU / Harvard Data Science Review", "url": "https://smu.edu/news/research/smu-researcher-develops-new-ai-tool-to-evaluate-wine" } ] }, { "id": 247, "catalogId": 254, "slug": "bored-gorilla-247", "url": "https://vinumexmachina.com/casebook/cases/#case-247", "nameRu": "Bored Gorilla", "nameEn": "Bored Gorilla", "operatorRu": "Schuler St. Jakobs Kellerei", "operatorEn": "Schuler St. Jakobs Kellerei", "countryRu": "Швейцария", "countryEn": "Switzerland", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "ch" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Первая этикетка, сгенерированная Midjourney; каждая бутылка привязана к NFT с 1/1000 изображения, пломбы NFC от Authena", "doesEn": "The first label generated by Midjourney; every bottle is tied to an NFT with 1/1000 of the image, NFC seals by Authena", "resultsRu": "1 000 магнумов, купаж 60% мерло и 40% темпранильо", "resultsEn": "1,000 magnums, a blend of 60% Merlot and 40% Tempranillo", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Falstaff", "url": "https://falstaff.com/en/news/bored-gorilla-the-first-ai-generated-wine-label" } ] }, { "id": 248, "catalogId": 255, "slug": "sommelier-bot-248", "url": "https://vinumexmachina.com/casebook/cases/#case-248", "nameRu": "Sommelier.bot", "nameEn": "Sommelier.bot", "operatorRu": "40+ ретейлеров, включая REWE, Obrist, City Drinks, OneHope Winery", "operatorEn": "40+ retailers, including REWE, Obrist, City Drinks, OneHope Winery", "countryRu": "США, Франция, Германия, Швейцария, Бразилия, ОАЭ", "countryEn": "United States, France, Germany, Switzerland, Brazil, United Arab Emirates", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us", "fr", "de", "ch", "br", "ae" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Чат-бот для интернет-магазинов, обогащает товары 30+ атрибутами вкуса и терруара, учится на истории покупок", "doesEn": "Chatbot for online shops; enriches products with 30+ taste and terroir attributes, learns from purchase history", "resultsRu": "По данным компании, 100 000+ активных пользователей, 40+ клиентов-мерчантов, 5 стран, €299 в месяц", "resultsEn": "According to the company, 100,000+ active users, 40+ merchant customers, 5 countries, €299 a month", "caveatRu": "Цифры приводятся по заявлению компании и независимо не подтверждены.", "caveatEn": "The figures are given as claimed by the company and are not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2026, "yearDisplay": "2023–2026", "yearRaw": "2023–2026", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Sommelier.bot", "url": "https://sommelier.bot" } ] }, { "id": 249, "catalogId": 256, "slug": "wine-engine-grapevineai-249", "url": "https://vinumexmachina.com/casebook/cases/#case-249", "nameRu": "Wine Engine «GrapevineAI»", "nameEn": "Wine Engine “GrapevineAI”", "operatorRu": "Подписной сервис", "operatorEn": "Subscription service", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "gb" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Чат-бот на OpenAI отвечает на вопросы, упрощает дегустационные заметки, предлагает сочетания", "doesEn": "An OpenAI-based chatbot answers questions, simplifies tasting notes, suggests pairings", "resultsRu": "Каталог из 400 вин на старте", "resultsEn": "A catalogue of 400 wines at launch", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "NationalWorld", "url": "https://www.nationalworld.com/lifestyle/food-and-drink/introducing-the-wine-engine-the-new-ai-powered-wine-platform-complete-with-virtual-sommelier-5212872" } ] }, { "id": 250, "catalogId": 257, "slug": "preferabli-tastefuli-v-napa-valley-marriott-250", "url": "https://vinumexmachina.com/casebook/cases/#case-250", "nameRu": "Preferabli «Tastefuli» в Napa Valley Marriott", "nameEn": "Preferabli “Tastefuli” at the Napa Valley Marriott", "operatorRu": "Гости отеля", "operatorEn": "Hotel guests", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Персональные рекомендации по вину, крепкому алкоголю, еде и местным впечатлениям, встроенные в работу консьержа", "doesEn": "Personal recommendations on wine, spirits, food and local experiences, built into the concierge's work", "resultsRu": "15 патентов у Preferabli, работа в 100 странах. Первое такое развёртывание в Напе.", "resultsEn": "15 patents held by Preferabli, operating in 100 countries. The first such deployment in Napa.", "caveatRu": "Основной источник недоступен; цифры подтверждены по другим публикациям.", "caveatEn": "The primary source is unavailable; the figures are confirmed from other publications.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Press Democrat", "url": "https://pressdemocrat.com/2025/12/02/napa-valley-marriott-preferabli-ai-concierge-wine-spirits-pairing" } ] }, { "id": 251, "catalogId": 258, "slug": "winespeak-ai-redchirp-251", "url": "https://vinumexmachina.com/casebook/cases/#case-251", "nameRu": "WineSpeak.ai + RedChirp", "nameEn": "WineSpeak.ai + RedChirp", "operatorRu": "Goosecross Cellars, Valle della Pace, Jessup Cellars", "operatorEn": "Goosecross Cellars, Valle della Pace, Jessup Cellars", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ИИ-консьерж «Goose» ведёт бронирования, записи в клуб и вопросы о сочетаниях круглосуточно, связка с SMS", "doesEn": "The AI concierge “Goose” handles bookings, club sign-ups and pairing questions around the clock, coupled with SMS", "resultsRu": "Открываемость SMS около 98%, конверсия 21–30% — примерно в десять раз выше email", "resultsEn": "SMS open rate about 98%, conversion 21–30% — roughly ten times higher than email", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Cork", "url": "https://www.hicork.com/news/ai-driven-concierge-tech-is-transforming-dtc-wine-sales" } ] }, { "id": 252, "catalogId": 259, "slug": "pinpointed-252", "url": "https://vinumexmachina.com/casebook/cases/#case-252", "nameRu": "Pinpointed", "nameEn": "Pinpointed", "operatorRu": "Applejack Wine & Spirits, Martins Off Licence, Premier Cru", "operatorEn": "Applejack Wine & Spirits, Martins Off Licence, Premier Cru", "countryRu": "США, Ирландия, Нидерланды", "countryEn": "United States, Ireland, Netherlands", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "us", "ie", "nl" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Отвечает на вопросы о сочетаниях и предлагает 2–3 позиции, реально имеющиеся в наличии", "doesEn": "Answers pairing questions and suggests 2–3 items that are actually in stock", "resultsRu": "Вендор заявляет +27,2% выручки на клиента и кликабельность 27,9% против отраслевых 2–5%. Пара $43,77 → $55,66 — это не средний чек, а «заявленный бюджет» против «цены кликнутого товара», как их определяет сам вендор.", "resultsEn": "The vendor claims +27.2% revenue per customer and a click-through rate of 27.9% against an industry 2–5%. The pair $43.77 → $55.66 is not average order value but “stated budget” against “price of the item clicked”, as the vendor itself defines them.", "caveatRu": "Все цифры — данные вендора по выборке из 102 сессий; методика не раскрыта.", "caveatEn": "All the figures are vendor data from a sample of 102 sessions; the methodology is not disclosed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Pinpointed", "url": "https://pinpointed.dev/wine-chatbot" } ] }, { "id": 253, "catalogId": 260, "slug": "sante-253", "url": "https://vinumexmachina.com/casebook/cases/#case-253", "nameRu": "Santé", "nameEn": "Santé", "operatorRu": "Сотни винных и алкогольных магазинов", "operatorEn": "Hundreds of wine and liquor shops", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "scaled", "country": [ "us" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Автоматизация сканирования накладных, учёта запасов, управления заказами и многоканальных коммуникаций", "doesEn": "Automation of invoice scanning, stock records, order management and multichannel communications", "resultsRu": "$7,6 млн seed-раунда (Bonfire Ventures, Y Combinator); рост 400% за год; обрабатывает более $500 млн годового карточного оборота.", "resultsEn": "$7.6m seed round (Bonfire Ventures, Y Combinator); 400% growth in a year; processes more than $500m of annual card turnover.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "TechStartups", "url": "https://techstartups.com/2026/02/12/sante-raises-7-6m-seed" } ] }, { "id": 254, "catalogId": 261, "slug": "wine-searcher-ai-254", "url": "https://vinumexmachina.com/casebook/cases/#case-254", "nameRu": "Wine-Searcher AI", "nameEn": "Wine-Searcher AI", "operatorRu": "Пользователи платформы", "operatorEn": "Platform users", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ИИ добавлен на платформу как отдельный «критик» наравне с людьми — под номером 124 в базе критиков", "doesEn": "AI added to the platform as a separate “critic” on a par with the human ones — number 124 in the critics database", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "Сайт источника блокирует автоматические запросы: существование продукта подтверждено косвенно, детали дословно не проверены.", "caveatEn": "The source site blocks automated requests: the product's existence is confirmed indirectly, the details have not been verified word for word.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Wine-Searcher", "url": "https://www.wine-searcher.com/m/2025/12/i-wine-searcher-a-critical-addition" } ] }, { "id": 255, "catalogId": 262, "slug": "third-aurora-255", "url": "https://vinumexmachina.com/casebook/cases/#case-255", "nameRu": "Third Aurora", "nameEn": "Third Aurora", "operatorRu": "Полевые испытания с 88 винодельнями в Австралии, США, Ливане, Израиле", "operatorEn": "Field trials with 88 wineries in Australia, the United States, Lebanon, Israel", "countryRu": "США, Австралия, Израиль, Ливан", "countryEn": "United States, Australia, Israel, Lebanon", "domain": "business", "tech": "llm", "stage": "pilot", "country": [ "us", "au", "il", "lb" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Распознавание и перевод этикеток, дегустационных заметок и промовидео", "doesEn": "Recognition and translation of labels, tasting notes and promotional video", "resultsRu": "88 виноделен в испытаниях, цель — более 100 языков", "resultsEn": "88 wineries in the trials, the target is more than 100 languages", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": 2019, "yearDisplay": "2019", "yearRaw": "2019", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Decanter", "url": "https://www.decanter.com/wine-news/wine-label-translator-app-launched-421098" } ] }, { "id": 256, "catalogId": 263, "slug": "opros-wine-spectator-kak-somele-realno-256", "url": "https://vinumexmachina.com/casebook/cases/#case-256", "nameRu": "Опрос Wine Spectator: как сомелье реально используют ИИ", "nameEn": "Wine Spectator survey: how sommeliers actually use AI", "operatorRu": "Сомелье ресторанов", "operatorEn": "Restaurant sommeliers", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Журналистское исследование повседневного применения: форматирование техлистов, ввод в POS, вычитка, учебные материалы, поиск по климату — но не дегустация и не рекомендации гостю", "doesEn": "A journalistic study of everyday use: formatting tech sheets, entry into the POS, proofreading, study materials, climate lookups — but not tasting and not recommendations to the guest", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Wine Spectator", "url": "https://www.winespectator.com/articles/ai-impact-restaurants-wine-sommeliers-diners-2025" } ] }, { "id": 257, "catalogId": 264, "slug": "dzho-roberts-1winedude-zadokumentirovannaya-257", "url": "https://vinumexmachina.com/casebook/cases/#case-257", "nameRu": "Джо Робертс (1WineDude): задокументированная галлюцинация", "nameEn": "Joe Roberts (1WineDude): a documented hallucination", "operatorRu": "Винный обозреватель", "operatorEn": "Wine columnist", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ИИ-инструмент, отвечая на вопрос о самом Робертсе, выдумал, что тот пишет для Forbes и Wine Enthusiast, и заявил, что он никогда не издавал книг о вине — хотя издал несколько", "doesEn": "Answering a question about Roberts himself, an AI tool invented that he writes for Forbes and Wine Enthusiast, and stated that he has never published a book on wine — though he has published several", "resultsRu": "Конкретный документированный случай", "resultsEn": "A specific documented case", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2025, "yearDisplay": "2023–2025", "yearRaw": "2023–2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "1WineDude", "url": "https://1winedude.com/fck-ai-with-a-cactus-thoughts-on-the-intersection-of-artificial-intelligence-and-wine" } ] }, { "id": 258, "catalogId": 265, "slug": "saymon-pevitt-na-inside-bordeaux-dzheyn-enson-258", "url": "https://vinumexmachina.com/casebook/cases/#case-258", "nameRu": "Саймон Пэвитт на Inside Bordeaux Джейн Энсон", "nameEn": "Simon Pavitt on Jane Anson's Inside Bordeaux", "operatorRu": "Отраслевая пресса", "operatorEn": "Trade press", "countryRu": "Франция, Великобритания", "countryEn": "France, United Kingdom", "domain": "business", "tech": "llm", "stage": "research", "country": [ "fr", "gb" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Статья о влиянии ИИ на винную журналистику, в конце которой автор раскрывает: 90% текста этой самой статьи написал ChatGPT", "doesEn": "An article on the effect of AI on wine journalism, at the end of which the author discloses that ChatGPT wrote 90% of the text of that same article", "resultsRu": "Самораскрытие: 90%", "resultsEn": "Self-disclosure: 90%", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Jane Anson", "url": "https://janeanson.com/chat-gpt-and-wine-extinction-level-event-for-wine-writers-and-sommeliers" } ] }, { "id": 259, "catalogId": 266, "slug": "rendi-kaparozo-behold-the-man-259", "url": "https://vinumexmachina.com/casebook/cases/#case-259", "nameRu": "Рэнди Капарозо, «Behold the Man»", "nameEn": "Randy Caparoso, “Behold the Man”", "operatorRu": "Wine Industry Advisor", "operatorEn": "Wine Industry Advisor", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "llm", "stage": "research", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Аргумент, что ИИ не воспроизводит человеческое восприятие вина: «ИИ не пьёт вино — люди пьют»; тренд на ремесленность как реакция на автоматизацию", "doesEn": "The argument that AI does not reproduce human perception of wine: “AI does not drink wine — people do”; a trend towards craft as a reaction to automation", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G5", "sectionRu": "G5. LLM и генеративный ИИ", "sources": [ { "name": "Wine Industry Advisor", "url": "https://wineindustryadvisor.com/2025/12/02/behold-the-man-ai-will-never-replace-human-perception-of-wine-oped" } ] }, { "id": 260, "catalogId": 267, "slug": "cerrion-v-verallia-260", "url": "https://vinumexmachina.com/casebook/cases/#case-260", "nameRu": "Cerrion в Verallia", "nameEn": "Cerrion at Verallia", "operatorRu": "Стекольный завод Verallia в Пеше", "operatorEn": "The Verallia glassworks at Pescia", "countryRu": "Италия (завод в Пеше)", "countryEn": "Italy (the Pescia plant)", "domain": "winemaking", "tech": "cv", "stage": "commercial", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Видеоаналитика распознаёт заторы, упавшие бутылки и аномалии линии, автоматически подаёт сигнал", "doesEn": "Video analytics recognises jams, fallen bottles and line anomalies, and raises an alert automatically", "resultsRu": "Время реакции на инцидент сокращено до 50%.", "resultsEn": "Incident response time reduced by up to 50%.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Glass International", "url": "https://www.glass-international.com/news/verallia-expands-cerrions-video-ai-at-pescia-glass-facility" } ] }, { "id": 261, "catalogId": 268, "slug": "commerce7-churn-prediction-261", "url": "https://vinumexmachina.com/casebook/cases/#case-261", "nameRu": "Commerce7 Churn Prediction", "nameEn": "Commerce7 Churn Prediction", "operatorRu": "Винодельни на платформе Commerce7", "operatorEn": "Wineries on the Commerce7 platform", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "international" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Предсказывает риск ухода члена винного клуба по обезличенным данным отрасли", "doesEn": "Predicts the risk of a wine club member leaving, from anonymised industry data", "resultsRu": "Точность 74%, обучение на «терабайтах» обезличенных данных", "resultsEn": "Accuracy 74%, trained on “terabytes” of anonymised data", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Wine Industry Advisor", "url": "https://wineindustryadvisor.com/2025/09/16/from-churn-prediction-to-chatdtc-commerce7-debuts-ai-features-built-for-dtc-growth/" } ] }, { "id": 262, "catalogId": 269, "slug": "commerce7-fraud-prediction-262", "url": "https://vinumexmachina.com/casebook/cases/#case-262", "nameRu": "Commerce7 Fraud Prediction", "nameEn": "Commerce7 Fraud Prediction", "operatorRu": "Те же", "operatorEn": "The same", "countryRu": "США", "countryEn": "United States", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "us" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Скоринг мошеннических заказов в реальном времени", "doesEn": "Real-time scoring of fraudulent orders", "resultsRu": "Удерживает уровень мошенничества ниже 0,025%.", "resultsEn": "Keeps the fraud rate below 0.025%.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Wine Industry Advisor", "url": "https://wineindustryadvisor.com/2025/09/16/from-churn-prediction-to-chatdtc-commerce7-debuts-ai-features-built-for-dtc-growth/" } ] }, { "id": 263, "catalogId": 270, "slug": "commerce7-chatdtc-posle-pokupki-winepulse-263", "url": "https://vinumexmachina.com/casebook/cases/#case-263", "nameRu": "Commerce7 ChatDTC (после покупки WinePulse)", "nameEn": "Commerce7 ChatDTC (after the WinePulse acquisition)", "operatorRu": "Винодельни на платформе Commerce7 (240+ виноделен — клиентская база WinePulse до покупки)", "operatorEn": "Wineries on the Commerce7 platform (240+ wineries — WinePulse's customer base before the acquisition)", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Запросы на естественном языке к 70 отчётам и 14 дашбордам", "doesEn": "Natural-language queries against 70 reports and 14 dashboards", "resultsRu": "Метрики всей платформы Commerce7: 60 000 заказов и 16 млн вызовов API в сутки", "resultsEn": "Metrics for the whole Commerce7 platform: 60,000 orders and 16m API calls a day", "caveatRu": "В источнике ChatDTC описан в будущем времени — как анонс, а не как работающая функция.", "caveatEn": "In the source ChatDTC is described in the future tense — as an announcement, not as a working feature.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Commerce7", "url": "https://www.commerce7.com/resources/commerce7-acquires-winepulse-bringing-industry-leading-analytics-to-wineries-worldwide" } ] }, { "id": 264, "catalogId": 271, "slug": "innovint-ai-analysis-import-264", "url": "https://vinumexmachina.com/casebook/cases/#case-264", "nameRu": "InnoVint AI Analysis Import", "nameEn": "InnoVint AI Analysis Import", "operatorRu": "Клиенты InnoVint", "operatorEn": "InnoVint customers", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "cv", "stage": "commercial", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Превращает фото рукописных записей и лабораторных бланков в структурированные данные", "doesEn": "Turns photographs of handwritten notes and laboratory forms into structured data", "resultsRu": "«Сотни документов, тысячи анализов»", "resultsEn": "“Hundreds of documents, thousands of analyses”", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "InnoVint", "url": "https://www.innovint.us/insight/intelligent-winery-workflows-powered-by-ai/" } ] }, { "id": 265, "catalogId": 272, "slug": "cork-supply-legacy-cork-265", "url": "https://vinumexmachina.com/casebook/cases/#case-265", "nameRu": "Cork Supply Legacy Cork", "nameEn": "Cork Supply Legacy Cork", "operatorRu": "Линия контроля DS100", "operatorEn": "The DS100 inspection line", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "winemaking", "tech": "cv", "stage": "commercial", "country": [ "pt" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Анализирует внутреннюю структуру каждой пробки, предсказывая кислородопроницаемость", "doesEn": "Analyses the internal structure of every cork, predicting oxygen permeability", "resultsRu": "По данным компании, ~14,5 млн пробок в год; около 222 человеко-часов в год — экономия на внутренней транспортировке, а не общая экономия труда", "resultsEn": "According to the company, ~14.5m corks a year; about 222 man-hours a year — a saving on internal transport, not an overall saving of labour", "caveatRu": "Цифры приводятся по заявлению компании и независимо не подтверждены.", "caveatEn": "The figures are given as claimed by the company and are not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/08/a-robotic-revolution-is-transforming-the-way-closures-are-made/" } ] }, { "id": 266, "catalogId": 273, "slug": "m-a-silva-onebyone-266", "url": "https://vinumexmachina.com/casebook/cases/#case-266", "nameRu": "M.A. Silva Onebyone", "nameEn": "M.A. Silva Onebyone", "operatorRu": "Линии M.A. Silva", "operatorEn": "M.A. Silva's lines", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "winemaking", "tech": "chemometrics", "stage": "commercial", "country": [ "pt" ], "confidence": "c", "aiKind": "borderline", "techRu": "", "techEn": "", "doesRu": "Газофазная спектроскопия и предиктивные модели, разработанные с Университетом Авейру, для поштучного скрининга на посторонние тона", "doesEn": "Gas-phase spectroscopy and predictive models developed with the University of Aveiro, for piece-by-piece screening for off-notes", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "Предиктивные модели по газофазной спектроскопии, разработанные с университетом; детали не раскрыты.", "whyEn": "Predictive models over gas-phase spectroscopy, developed with a university; the details are not disclosed.", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/08/a-robotic-revolution-is-transforming-the-way-closures-are-made/" } ] }, { "id": 267, "catalogId": 274, "slug": "amorim-opticheskaya-sortirovka-probki-267", "url": "https://vinumexmachina.com/casebook/cases/#case-267", "nameRu": "Amorim: оптическая сортировка пробки", "nameEn": "Amorim: optical cork sorting", "operatorRu": "Линии Amorim", "operatorEn": "Amorim's lines", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "winemaking", "tech": "cv", "stage": "commercial", "country": [ "pt" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Классификация пробок по тысячам изображений тела и головки", "doesEn": "Classification of corks from thousands of images of the body and the head", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "Классификация пробок по изображениям — по расширенному определению это ИИ.", "whyEn": "Classification of corks from images — AI under the broader definition.", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2025/08/a-robotic-revolution-is-transforming-the-way-closures-are-made/" } ] }, { "id": 268, "catalogId": 275, "slug": "winegrid-watgrid-268", "url": "https://vinumexmachina.com/casebook/cases/#case-268", "nameRu": "Winegrid (WATGRID)", "nameEn": "Winegrid (WATGRID)", "operatorRu": "Производители, включая группу Sogrape", "operatorEn": "Producers, including the Sogrape group", "countryRu": "США, Франция, Италия, Австралия, Испания, Португалия, ЮАР, Чили, Аргентина", "countryEn": "United States, France, Italy, Australia, Spain, Portugal, South Africa, Chile, Argentina", "domain": "winemaking", "tech": "sensors-iot", "stage": "commercial", "country": [ "us", "fr", "it", "au", "es", "pt", "za", "cl", "ar" ], "confidence": "b", "aiKind": "borderline", "techRu": "", "techEn": "", "doesRu": "Датчики плотности, температуры, цвета и мутности в ёмкостях, бочках и прессах с автоматическим выявлением событий", "doesEn": "Density, temperature, colour and turbidity sensors in tanks, barrels and presses, with automatic event detection", "resultsRu": "Маркетинг заявляет более 150 млн бутылок, произведённых с использованием системы; грант ЕС €50 000.", "resultsEn": "Marketing claims more than 150m bottles produced using the system; an EU grant of €50,000.", "caveatRu": "", "caveatEn": "", "whyRu": "Автоматическое выявление событий во временных рядах датчиков; глубина модели не раскрыта.", "whyEn": "Automatic event detection in sensor time series; the depth of the model is not disclosed.", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": null, "yearDisplay": "2018–", "yearRaw": "2018–", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Winegrid", "url": "https://www.winegrid.com/en/" }, { "name": "CORDIS", "url": "https://cordis.europa.eu/project/id/832214" } ] }, { "id": 269, "catalogId": 276, "slug": "membrannyy-press-della-toffola-269", "url": "https://vinumexmachina.com/casebook/cases/#case-269", "nameRu": "Мембранный пресс Della Toffola", "nameEn": "Della Toffola membrane press", "operatorRu": "Винодельни", "operatorEn": "Wineries", "countryRu": "ЮАР", "countryEn": "South Africa", "domain": "winemaking", "tech": "sensors-iot", "stage": "commercial", "country": [ "za" ], "confidence": "c", "aiKind": "borderline", "techRu": "", "techEn": "", "doesRu": "Оптимизация цикла прессования по датчикам веса, потока и колориметрии с разделением фракций сусла по качеству", "doesEn": "Optimisation of the pressing cycle from weight, flow and colorimetry sensors, with separation of must fractions by quality", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "Оптимизация цикла прессования по датчикам; «нейросеть» упомянута в единственном интервью и на страницах продукта не подтверждается.", "whyEn": "Optimisation of the pressing cycle from sensors; the “neural network” is mentioned in a single interview and is not confirmed on the product pages.", "dataRu": "", "dataEn": "", "yearStart": 2021, "yearEnd": null, "yearDisplay": "2021–", "yearRaw": "2021–", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Wine Industry Advisor", "url": "https://wineindustryadvisor.com/2021/01/17/della-toffola-takes-smart-pressing-to-a-new-level/" } ] }, { "id": 270, "catalogId": 277, "slug": "oculyze-fermentation-wine-270", "url": "https://vinumexmachina.com/casebook/cases/#case-270", "nameRu": "Oculyze Fermentation Wine", "nameEn": "Oculyze Fermentation Wine", "operatorRu": "Винодельни", "operatorEn": "Wineries", "countryRu": "США, Франция, Италия, Австралия, Испания, Германия, Португалия, Новая Зеландия, Чили, Канада, Румыния", "countryEn": "United States, France, Italy, Australia, Spain, Germany, Portugal, New Zealand, Chile, Canada, Romania", "domain": "winemaking", "tech": "cv", "stage": "commercial", "country": [ "us", "fr", "it", "au", "es", "de", "pt", "nz", "cl", "ca", "ro" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Автоматический подсчёт клеток дрожжей, жизнеспособности и почкования вместо ручной камеры Горяева", "doesEn": "Automatic counting of yeast cells, viability and budding in place of a manual haemocytometer", "resultsRu": "«В десять раз быстрее ручного счёта»; диапазон 8,5×10⁵–3,5×10⁷ клеток/мл", "resultsEn": "“Ten times faster than manual counting”; range 8.5×10⁵–3.5×10⁷ cells/ml", "caveatRu": "На страницах самого продукта вендор описывает технологию как распознавание изображений и не заявляет ни ИИ, ни машинное обучение; в другом разделе своего сайта он называет базовую технологию своих счётчиков дрожжей, включая Fermentation Wine, сочетанием распознавания образов с ИИ и глубоким обучением.", "caveatEn": "On the product's own pages the vendor describes the technology as image recognition and claims neither AI nor machine learning; elsewhere on its site it describes the base technology of its yeast cell counters, Fermentation Wine included, as pattern recognition combined with AI and deep learning.", "whyRu": "Распознавание изображений — по расширенному определению это ИИ.", "whyEn": "Image recognition — AI under the broader definition.", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "G6", "sectionRu": "G6. Погреб, упаковка, ПО", "sources": [ { "name": "Oculyze", "url": "https://www.oculyze.net/yeast-cell-counter/wine-fermentation/how-it-works/" }, { "name": "Oculyze — Best Pattern Recognition Software", "url": "https://www.oculyze.net/best-pattern-recognition-software/" } ] }, { "id": 271, "catalogId": 278, "slug": "frost-weatherquest-winegb-271", "url": "https://vinumexmachina.com/casebook/cases/#case-271", "nameRu": "FROST (WeatherQuest + WineGB)", "nameEn": "FROST (WeatherQuest + WineGB)", "operatorRu": "Виноградники Англии и Уэльса, Plumpton College", "operatorEn": "Vineyards of England and Wales, Plumpton College", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "viticulture", "tech": "disease-weather", "stage": "pilot", "country": [ "gb" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ML и сенсорные данные дают прогноз риска заморозка с привязкой к участку и сорту, объединяя модель распускания почек с рельефом", "doesEn": "ML and sensor data give a frost-risk forecast tied to the site and the grape variety, combining a budburst model with terrain", "resultsRu": "£300 000 от Innovate UK и Defra", "resultsEn": "£300,000 from Innovate UK and Defra", "caveatRu": "Сумма £300 000 подтверждается другим изданием — на цитируемой странице её нет.", "caveatEn": "The £300,000 figure is confirmed by a different publication — it is not on the page cited.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2025, "yearDisplay": "2024–2025", "yearRaw": "2024–2025", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "UK Agri-Tech Centre", "url": "https://ukagritechcentre.com/project/smarter-forecasting-communication-management-frost-risk-vineyards-frost/" } ] }, { "id": 272, "catalogId": 279, "slug": "autopickr-vinny-272", "url": "https://vinumexmachina.com/casebook/cases/#case-272", "nameRu": "Autopickr «Vinny»", "nameEn": "Autopickr “Vinny”", "operatorRu": "Coopers Croft Vineyard, при поддержке WineGB", "operatorEn": "Coopers Croft Vineyard, supported by WineGB", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "viticulture", "tech": "robotics", "stage": "research", "country": [ "gb" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Система машинного зрения на автономном роботе отличает зрелые грозди от незрелых для ручного по качеству сбора целыми гроздями", "doesEn": "A machine-vision system on an autonomous robot distinguishes ripe bunches from unripe ones for whole-bunch harvesting at hand-picked quality", "resultsRu": "£475 000 государственного финансирования. Контекст: 1 033 виноградника и 4 209 га в стране, рост 123% за десятилетие.", "resultsEn": "£475,000 of public funding. Context: 1,033 vineyards and 4,209 ha in the country, up 123% over the decade.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2024/12/british-wine-industry-secures-government-funding-for-robotics-project/" } ] }, { "id": 273, "catalogId": 280, "slug": "naked-wines-273", "url": "https://vinumexmachina.com/casebook/cases/#case-273", "nameRu": "Naked Wines", "nameEn": "Naked Wines", "operatorRu": "Naked Wines plc", "operatorEn": "Naked Wines plc", "countryRu": "США, Австралия, Великобритания", "countryEn": "United States, Australia, United Kingdom", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "us", "au", "gb" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ML-модель прогнозирует вклад клиента на горизонте пяти лет по демографии, взаимодействиям и транзакциям, определяя, кого набирать и сколько в него вложить", "doesEn": "An ML model forecasts a customer's contribution over a five-year horizon from demographics, interactions and transactions, determining whom to recruit and how much to invest in them", "resultsRu": "35,6 млн клиентских отзывов в основе рекомендаций; прогнозная пятилетняя окупаемость затрат на новых клиентов 1,7x; 14 лет собственных поведенческих данных", "resultsEn": "35.6m customer reviews behind its recommendations; a forecast five-year payback of 1.7x on new-customer spend; 14 years of proprietary behavioural data", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "Годовой отчёт Naked Wines 2023", "url": "https://s28.q4cdn.com/964621086/files/doc_financials/2023/ar/NakedWines_AR23_FINAL.pdf" } ] }, { "id": 274, "catalogId": 281, "slug": "vinemap-vinescapes-274", "url": "https://vinumexmachina.com/casebook/cases/#case-274", "nameRu": "VineMAP (Vinescapes)", "nameEn": "VineMAP (Vinescapes)", "operatorRu": "Разработчики виноградников", "operatorEn": "Vineyard developers", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "viticulture", "tech": "disease-weather", "stage": "commercial", "country": [ "gb" ], "confidence": "b", "aiKind": "borderline", "techRu": "", "techEn": "", "doesRu": "Моделирование пригодности участка по высоте, экспозиции, солнечной радиации, почвам и климату; методология опубликована в рецензируемом журнале", "doesEn": "Site suitability modelling from elevation, aspect, solar radiation, soils and climate; the methodology is published in a peer-reviewed journal", "resultsRu": "Числа клиентов не раскрыты.", "resultsEn": "Customer numbers are not disclosed.", "caveatRu": "Вендор не заявляет ни ИИ, ни машинное обучение: на его странице это описано как геопространственный ГИС-анализ.", "caveatEn": "The vendor claims neither AI nor machine learning: its page describes this as geospatial GIS analysis.", "whyRu": "Предиктивное моделирование пригодности участка с рецензируемой методологией, но обучаемой модели вендор не заявляет.", "whyEn": "Predictive site-suitability modelling with a peer-reviewed methodology, but the vendor claims no trained model.", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "VineMAP", "url": "https://www.vinemap.com/" } ] }, { "id": 275, "catalogId": 282, "slug": "crews-uk-275", "url": "https://vinumexmachina.com/casebook/cases/#case-275", "nameRu": "CREWS-UK", "nameEn": "CREWS-UK", "operatorRu": "Консорциум UEA, LSE Grantham, Vinescapes, WeatherQuest", "operatorEn": "Consortium of UEA, LSE Grantham, Vinescapes, WeatherQuest", "countryRu": "Великобритания", "countryEn": "United Kingdom", "domain": "viticulture", "tech": "disease-weather", "stage": "research", "country": [ "gb" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Моделирование пригодности сортов и стилей и сдвига рисков заморозка до 2050 года", "doesEn": "Modelling of grape-variety and style suitability and of the shift in frost risk to 2050", "resultsRu": "Площадь виноградников выросла с 761 до 3 800 га за 2004–2021, около +400%; температура вегетационного периода прогнозируется +1,4 °C к 2021–2040.", "resultsEn": "Vineyard area grew from 761 to 3,800 ha over 2004–2021, about +400%; growing-season temperature is forecast at +1.4 °C by 2021–2040.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2022, "yearDisplay": "2022", "yearRaw": "2022", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "UEA", "url": "https://www.uea.ac.uk/about/news/article/study-predicts-growth-in-uk-wine-production-due-to-climate-change" } ] }, { "id": 276, "catalogId": 283, "slug": "rathfinny-estate-276", "url": "https://vinumexmachina.com/casebook/cases/#case-276", "nameRu": "Rathfinny Estate", "nameEn": "Rathfinny Estate", "operatorRu": "Rathfinny Estate", "operatorEn": "Rathfinny Estate", "countryRu": "Великобритания (Сассекс)", "countryEn": "United Kingdom (Sussex)", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "gb" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "ML-анализ видео с обычных проходов косилки извлекает число гроздей и высоту побегов на лозу; отдельный вендор оценивает рост полога и зрелость в приложении; дроновое 3D-картирование от Imperial College", "doesEn": "ML analysis of video from routine mower passes extracts bunch counts and shoot height per vine; a separate vendor assesses canopy growth and ripeness in an app; drone 3D mapping from Imperial College", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2029, "yearDisplay": "2020–2029", "yearRaw": "2020-е", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "Rathfinny", "url": "https://rathfinnyestate.com/about/news/emerging-vineyard-technology/" } ] }, { "id": 277, "catalogId": 284, "slug": "systembolaget-277", "url": "https://vinumexmachina.com/casebook/cases/#case-277", "nameRu": "Systembolaget", "nameEn": "Systembolaget", "operatorRu": "Клиенты приложения государственной монополии", "operatorEn": "Customers of the state monopoly's app", "countryRu": "Швеция", "countryEn": "Sweden", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "se" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Модель схожести «Liknande vin» — «сомелье в кармане» — подбирает вина, близкие по вкусу и аромату, с учётом объёма бутылки; генеративный ИИ улучшил поиск по товарам", "doesEn": "The “Liknande vin” similarity model — a “sommelier in your pocket” — finds wines close in taste and aroma, taking bottle volume into account; generative AI improved product search", "resultsRu": "Полный цифровой ассортимент развёрнут в 115 магазинах к третьему кварталу 2024.", "resultsEn": "The full digital range was rolled out in 115 stores by the third quarter of 2024.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2022, "yearEnd": 2024, "yearDisplay": "2022–2024", "yearRaw": "2022, 2024", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "Systembolaget", "url": "https://press.systembolaget.se/pressmeddelanden/2024/delarsrapport-kvartal-3-utveckling-av-det-digitala-kunderbjudandet-med-ai/" } ] }, { "id": 278, "catalogId": 285, "slug": "winevizer-278", "url": "https://vinumexmachina.com/casebook/cases/#case-278", "nameRu": "Winevizer", "nameEn": "Winevizer", "operatorRu": "Рестораны и винные бары", "operatorEn": "Restaurants and wine bars", "countryRu": "США, Франция, Швейцария, Бельгия", "countryEn": "United States, France, Switzerland, Belgium", "domain": "business", "tech": "recommender", "stage": "commercial", "country": [ "us", "fr", "ch", "be" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Виртуальный сомелье, работающий по правилам и сверяющийся с реальными остатками погреба, а не открытый чат-бот", "doesEn": "A virtual sommelier that works to rules and checks against actual cellar stock, not an open chatbot", "resultsRu": "Заявлено +15–30% проданных бутылок, +25% среднего чека по вину, время выбора сокращено с 90 до 25 секунд.", "resultsEn": "Claimed +15–30% bottles sold, +25% average wine bill, choosing time cut from 90 to 25 seconds.", "caveatRu": "Цифры приводятся по заявлению вендора; ни одно заведение как клиент источником не названо.", "caveatEn": "The figures are given on the vendor's claim; the source names no venue as a customer.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "Winevizer", "url": "https://www.winevizer.com/en/virtual-sommelier" } ] }, { "id": 279, "catalogId": 287, "slug": "binwise-ingest-ai-winedirect-insights-279", "url": "https://vinumexmachina.com/casebook/cases/#case-279", "nameRu": "BinWise, Ingest AI, WineDirect Insights", "nameEn": "BinWise, Ingest AI, WineDirect Insights", "operatorRu": "Рестораны, отели, бары", "operatorEn": "Restaurants, hotels, bars", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "optimisation", "stage": "commercial", "country": [ "international" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Предиктивная аналитика закупок, списаний и риска порчи", "doesEn": "Predictive analytics for purchasing, write-offs and spoilage risk", "resultsRu": "Независимо подтверждённых цифр нет.", "resultsEn": "There are no independently confirmed figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": null, "yearEnd": null, "yearDisplay": "—", "yearRaw": "—", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "Sommelier Business", "url": "https://sommelierbusiness.com/en/articles/operations-and-management-10/how-ai-data-analytics-are-changing-wine-menus-and-sales-forecasting-749.htm" } ] }, { "id": 280, "catalogId": 288, "slug": "llm-kak-uchebnyy-instrument-dlya-wset-diploma-280", "url": "https://vinumexmachina.com/casebook/cases/#case-280", "nameRu": "LLM как учебный инструмент для WSET Diploma", "nameEn": "LLM as a study tool for the WSET Diploma", "operatorRu": "Кандидаты WSET", "operatorEn": "WSET candidates", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "international" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Студенты используют универсальные модели для конспектирования теории и карточек; преподаватели уровня MW публично предостерегают от чрезмерной опоры", "doesEn": "Students use general-purpose models to summarise theory and make flashcards; MW-level teachers publicly warn against over-reliance", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "Источником подтверждена только рекомендация Master of Wine использовать LLM для карточек.", "caveatEn": "All the source confirms is a Master of Wine's recommendation to use an LLM for flashcards.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "2024", "sectionKey": "G7", "sectionRu": "G7. UK, Канада, Скандинавия, гостеприимство", "sources": [ { "name": "The Drinks Business", "url": "https://www.thedrinksbusiness.com/2024/10/five-ways-ai-is-impacting-the-wine-trade/" } ] }, { "id": 281, "catalogId": 289, "slug": "fieldin-281", "url": "https://vinumexmachina.com/casebook/cases/#case-281", "nameRu": "Fieldin", "nameEn": "Fieldin", "operatorRu": "Виноградники и сады", "operatorEn": "Vineyards and orchards", "countryRu": "США, Австралия, Израиль", "countryEn": "United States, Australia, Israel", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "us", "au", "il" ], "confidence": "b", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Платформа управления полевыми операциями: телеметрия машин, контроль обработок, точное опрыскивание с ARAG; виноград прямо указан среди поддерживаемых культур", "doesEn": "Field-operations management platform: machine telemetry, monitoring of treatments, precision spraying with ARAG; grapes are explicitly listed among the supported crops", "resultsRu": "750 000+ акров под управлением по всем культурам", "resultsEn": "750,000+ acres under management across all crops", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "Fieldin", "url": "https://fieldin.com/resources/" } ] }, { "id": 282, "catalogId": 290, "slug": "programma-vinogradarstva-v-pustyne-negev-282", "url": "https://vinumexmachina.com/casebook/cases/#case-282", "nameRu": "Программа виноградарства в пустыне Негев", "nameEn": "Negev desert viticulture programme", "operatorRu": "Nana Estate, Carmey Avdat и 30+ виноградников Негева; работа по сортам — Ариэльский университет", "operatorEn": "Nana Estate, Carmey Avdat and 30+ Negev vineyards; grape-variety work by Ariel University", "countryRu": "Израиль", "countryEn": "Israel", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "il" ], "confidence": "b", "aiKind": "adjacent", "techRu": "", "techEn": "", "doesRu": "Полив из смартфона, селекция солеустойчивых подвоев, датчики корневой зоны", "doesEn": "Irrigation from a smartphone, breeding of salt-tolerant rootstocks, root-zone sensors", "resultsRu": "Более 30 действующих виноградников при 250–280 мм осадков в год; Ариэльский университет отобрал 6 перспективных сортов из 600+ образцов дикого винограда.", "resultsEn": "More than 30 working vineyards on 250–280 mm of rainfall a year; Ariel University selected 6 promising grape varieties from 600+ samples of wild grapevine.", "caveatRu": "ИИ-компоненты в источнике нет: описаны полив со смартфона и классическая селекция.", "caveatEn": "There is no AI component in the source: it describes smartphone irrigation and classical breeding.", "whyRu": "Полив со смартфона и классическая селекция подвоев. ИИ-компонента в источнике нет вовсе.", "whyEn": "Smartphone irrigation and classical rootstock breeding. There is no AI component in the source at all.", "dataRu": "", "dataEn": "", "yearStart": 2019, "yearEnd": null, "yearDisplay": "2019–", "yearRaw": "2019–", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "Smithsonian", "url": "https://www.smithsonianmag.com/travel/wines-israel-negev-desert-represent-future-viticulture-180974590/" } ] }, { "id": 283, "catalogId": 291, "slug": "netafim-netbeat-283", "url": "https://vinumexmachina.com/casebook/cases/#case-283", "nameRu": "Netafim NetBeat", "nameEn": "Netafim NetBeat", "operatorRu": "Точное орошение (виноградное применение в источнике не названо)", "operatorEn": "Precision irrigation (no vineyard application named in the source)", "countryRu": "Весь мир", "countryEn": "International", "domain": "viticulture", "tech": "sensors-iot", "stage": "commercial", "country": [ "international" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Облачный «агромозг» объединяет сенсорику, поддержку решений и автоматическое управление капельным поливом", "doesEn": "A cloud “agro-brain” combines sensing, decision support and automatic control of drip irrigation", "resultsRu": "Экономия воды 20–50%, плюс 15–20% времени на мониторинг; 150 штатных агрономов", "resultsEn": "Water savings of 20–50%, plus 15–20% of monitoring time; 150 agronomists on staff", "caveatRu": "Экономия относится к капельному орошению по всем культурам; виноград в источнике не упоминается.", "caveatEn": "The savings relate to drip irrigation across all crops; grapes are not mentioned in the source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": null, "yearDisplay": "2017–", "yearRaw": "2017–", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "Israel Agri", "url": "https://israelagri.com/the-first-irrigation-system-with-a-brain/" } ] }, { "id": 284, "catalogId": 292, "slug": "konferentsiya-po-generativnomu-ii-icar-nrcg-284", "url": "https://vinumexmachina.com/casebook/cases/#case-284", "nameRu": "Конференция по генеративному ИИ ICAR-NRCG", "nameEn": "ICAR-NRCG generative AI conference", "operatorRu": "Национальный исследовательский центр по винограду (Пуна)", "operatorEn": "National Research Centre for Grapes (Pune)", "countryRu": "Индия", "countryEn": "India", "domain": "viticulture", "tech": "llm", "stage": "research", "country": [ "in" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Национальная конференция по применению генеративного ИИ в аграрных исследованиях", "doesEn": "A national conference on the use of generative AI in agricultural research", "resultsRu": "130 исследователей, 30 лекций, 6 пленарных докладов", "resultsEn": "130 researchers, 30 lectures, 6 plenary talks", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "ICAR", "url": "https://icar.org.in/en/icar-nrc-grapes-organises-national-conference-generative-ai" } ] }, { "id": 285, "catalogId": 293, "slug": "tsifrovoe-vinogradarstvo-icar-nrcg-285", "url": "https://vinumexmachina.com/casebook/cases/#case-285", "nameRu": "Цифровое виноградарство ICAR-NRCG", "nameEn": "ICAR-NRCG digital viticulture", "operatorRu": "Виноградные регионы Индии", "operatorEn": "India's grape-growing regions", "countryRu": "Индия", "countryEn": "India", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "in" ], "confidence": "a", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "IoT-датчики, дроновая и спутниковая съёмка, автоматические рекомендации, детекция стресса", "doesEn": "IoT sensors, drone and satellite imagery, automated recommendations, stress detection", "resultsRu": "Цифр внедрения нет. Названные барьеры: высокие первоначальные затраты, дефицит компетенций, проблемы с управлением данными.", "resultsEn": "There are no adoption figures. The barriers named: high up-front costs, a shortage of skills, data-management problems.", "caveatRu": "Источник описывает Индию в целом и называет ИИ в общем перечне, без технических деталей.", "caveatEn": "The source describes India as a whole and names AI in a general list, with no technical detail.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "Indian Horticulture", "url": "https://epubs.icar.org.in/index.php/IndHort/article/view/163658" } ] }, { "id": 286, "catalogId": 294, "slug": "space-ag-raptorview-286", "url": "https://vinumexmachina.com/casebook/cases/#case-286", "nameRu": "Space AG RaptorView", "nameEn": "Space AG RaptorView", "operatorRu": "Перуанские производители винограда", "operatorEn": "Peruvian grape growers", "countryRu": "Перу", "countryEn": "Peru", "domain": "viticulture", "tech": "remote-sensing", "stage": "commercial", "country": [ "pe" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Спутниковый мониторинг и полевой сбор данных", "doesEn": "Satellite monitoring and field data collection", "resultsRu": "Независимых цифр нет.", "resultsEn": "There are no independent figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "Redagricola", "url": "https://redagricola.com/viticultura-3-0-mas-eficiencia-y-precision-en-la-produccion/" } ] }, { "id": 287, "catalogId": 295, "slug": "austral-falcon-287", "url": "https://vinumexmachina.com/casebook/cases/#case-287", "nameRu": "Austral Falcon", "nameEn": "Austral Falcon", "operatorRu": "Производители винограда", "operatorEn": "Grape growers", "countryRu": "Чили", "countryEn": "Chile", "domain": "viticulture", "tech": "yield", "stage": "commercial", "country": [ "cl" ], "confidence": "c", "aiKind": "yes", "techRu": "", "techEn": "", "doesRu": "Наземное устройство с камерами и GPS автоматически считает грозди для прогноза урожая", "doesEn": "A ground-based device with cameras and GPS counts bunches automatically for yield forecasting", "resultsRu": "Вендор заявляет точность прогноза 95%.", "resultsEn": "The vendor claims 95% forecast accuracy.", "caveatRu": "Цифра приводится по заявлению компании и независимо не подтверждена.", "caveatEn": "The figure is given on the company's claim and is not independently confirmed.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2026, "yearDisplay": "2025–2026", "yearRaw": "2025–2026", "sectionKey": "G8", "sectionRu": "G8. Израиль, Индия, Латинская Америка", "sources": [ { "name": "Redagricola", "url": "https://redagricola.com/viticultura-3-0-mas-eficiencia-y-precision-en-la-produccion/" } ] }, { "id": 288, "catalogId": 296, "slug": "kompyuternoe-zrenie-v-vinogradarstve-kfu-288", "url": "https://vinumexmachina.com/casebook/cases/#case-288", "nameRu": "Компьютерное зрение в виноградарстве (КФУ + «Коктебель»)", "nameEn": "Computer vision in viticulture (Crimean Federal University + Koktebel)", "operatorRu": "Крымский федеральный университет, винодельня «Коктебель», Феодосия", "operatorEn": "Crimean Federal University, Koktebel winery, Feodosia", "countryRu": "Россия (Крым)", "countryEn": "Russia (Crimea)", "domain": "viticulture", "tech": "cv", "stage": "pilot", "country": [ "ru" ], "confidence": "b", "aiKind": "yes", "techRu": "Свёрточные сети для распознавания болезней по фото + роботизированная линия прививки", "techEn": "Convolutional networks for recognising diseases from photographs + a robotic grafting line", "doesRu": "Определение болезни по снимку, присланному виноградарем; автоматизация производства посадочного материала", "doesEn": "Identifying a disease from an image sent in by a grower; automation of planting-material production", "resultsRu": "Завершение работ планировалось к концу 2023; показателей точности и внедрения не опубликовано.", "resultsEn": "The work was scheduled for completion by the end of 2023; no accuracy or adoption figures have been published.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2023, "yearDisplay": "2023", "yearRaw": "2023", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "РИА Крым", "url": "https://crimea.ria.ru/20230206/tsifrovye-vinogradniki-chto-eto-takoe-i-zachem-oni-rossii-1126708200.html" } ] }, { "id": 289, "catalogId": 297, "slug": "doctorp-oiyai-dubna-289", "url": "https://vinumexmachina.com/casebook/cases/#case-289", "nameRu": "DoctorP (ОИЯИ, Дубна)", "nameEn": "DoctorP (JINR, Dubna)", "operatorRu": "Общедоступное приложение; 19 культур, включая виноград", "operatorEn": "A publicly available app; 19 crops, including grapes", "countryRu": "Россия", "countryEn": "Russia", "domain": "viticulture", "tech": "cv", "stage": "commercial", "country": [ "ru" ], "confidence": "b", "aiKind": "yes", "techRu": "Свёрточная сеть с переносом обучения", "techEn": "Convolutional network with transfer learning", "doesRu": "Диагностика болезней и вредителей по фотографии листа через мобильное и веб-приложение", "doesEn": "Diagnosis of diseases and pests from a photograph of a leaf, through a mobile and web app", "resultsRu": "Ранняя модель, обученная на синтетических изображениях из открытых баз, давала на них точность выше 95% — но на реальных пользовательских фотографиях точность падала примерно до 50%. После того как команда собрала собственную базу полевых снимков и перестроила модели, их точность держится выше 95% при более чем 50 классах. 55–60 классов болезней и вредителей; 4 000+ обучающих изображений; более 40 000 обращений накопительно (не в год); более 10 000 пользователей Android-приложения. Виноград прямо назван среди 19 культур.", "resultsEn": "An early model, trained on synthetic images from open datasets, scored above 95% accuracy on them — but on real user photographs its accuracy fell to roughly 50%. After the team collected its own base of field photographs and rebuilt the models, their accuracy holds above 95% with more than 50 classes. 55–60 classes of diseases and pests; 4,000+ training images; more than 40,000 queries cumulatively (not per year); more than 10,000 users of the Android app. Grapes are explicitly named among the 19 crops.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2017, "yearEnd": 2023, "yearDisplay": "2017–2023", "yearRaw": "2017–2023", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Научная Россия", "url": "https://scientificrussia.ru/articles/oiai-razvivaet-platformu-dla-raspoznavania-boleznej-rastenij" } ] }, { "id": 290, "catalogId": 298, "slug": "vintellekt-vino-ru-gureev-pro-290", "url": "https://vinumexmachina.com/casebook/cases/#case-290", "nameRu": "ВИНТЕЛЛЕКТ (Vino.ru + Gureev.Pro)", "nameEn": "VINTELLEKT (Vino.ru + Gureev.Pro)", "operatorRu": "Маркетплейс Vino.ru", "operatorEn": "The Vino.ru marketplace", "countryRu": "Россия", "countryEn": "Russia", "domain": "business", "tech": "llm", "stage": "commercial", "country": [ "ru" ], "confidence": "b", "aiKind": "yes", "techRu": "Дообученная YandexGPT 3 Pro + семантический поиск по каталогу", "techEn": "Fine-tuned YandexGPT 3 Pro + semantic search over the catalogue", "doesRu": "Телеграм-бот-сомелье: распознаёт в свободном запросе тип, сахар, крепость и ароматику, возвращает три вина с обоснованием", "doesEn": "A Telegram sommelier bot: it picks out type, sugar, strength and aromatics from a free-text request and returns three wines with reasons", "resultsRu": "Обучен на 1 000+ реальных клиентских запросов при участии профессиональных сомелье.", "resultsEn": "Trained on 1,000+ real customer requests with professional sommeliers involved.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2024, "yearEnd": 2024, "yearDisplay": "2024", "yearRaw": "июнь 2024", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "CNews", "url": "https://www.cnews.ru/news/line/2024-06-10_marketplejs_vinoru_zapustil" } ] }, { "id": 291, "catalogId": 299, "slug": "abrau-dyurso-291", "url": "https://vinumexmachina.com/casebook/cases/#case-291", "nameRu": "«Абрау-Дюрсо»", "nameEn": "Abrau-Durso", "operatorRu": "«Абрау-Дюрсо»", "operatorEn": "Abrau-Durso", "countryRu": "Россия", "countryEn": "Russia", "domain": "viticulture", "tech": "optimisation", "stage": "unconfirmed", "country": [ "ru" ], "confidence": "c", "aiKind": "yes", "techRu": "Мониторинг виноградников, прогноз спроса на моделях Сбера", "techEn": "Vineyard monitoring, demand forecasting on Sber models", "doesRu": "Заявлено применение ИИ в мониторинге виноградников, логистике и прогнозировании спроса", "doesEn": "Claimed use of AI in vineyard monitoring, logistics and demand forecasting", "resultsRu": "Ни методологии, ни цифр не раскрыто.", "resultsEn": "Neither methodology nor figures have been disclosed.", "caveatRu": "Запись опирается на единственный источник.", "caveatEn": "The record rests on a single source.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Habr", "url": "https://habr.com/ru/articles/910880/" } ] }, { "id": 292, "catalogId": 300, "slug": "kuban-vino-292", "url": "https://vinumexmachina.com/casebook/cases/#case-292", "nameRu": "«Кубань-Вино»", "nameEn": "Kuban-Vino", "operatorRu": "«Кубань-Вино»", "operatorEn": "Kuban-Vino", "countryRu": "Россия", "countryEn": "Russia", "domain": "winemaking", "tech": "cv", "stage": "research", "country": [ "ru" ], "confidence": "c", "aiKind": "yes", "techRu": "Машинное зрение на линии розлива + внутренний ИИ-ассистент по документам", "techEn": "Machine vision on the bottling line + an internal AI assistant for documents", "doesRu": "Выявление дефектов при розливе", "doesEn": "Detection of defects during bottling", "resultsRu": "Запуск заявлен на третий квартал 2025; результатов нет.", "resultsEn": "Launch is claimed for the third quarter of 2025; there are no results.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Habr", "url": "https://habr.com/ru/articles/910880/" } ] }, { "id": 293, "catalogId": 301, "slug": "fanagoriya-293", "url": "https://vinumexmachina.com/casebook/cases/#case-293", "nameRu": "«Фанагория»", "nameEn": "Fanagoria", "operatorRu": "«Фанагория»", "operatorEn": "Fanagoria", "countryRu": "Россия", "countryEn": "Russia", "domain": "business", "tech": "llm", "stage": "pilot", "country": [ "ru" ], "confidence": "c", "aiKind": "yes", "techRu": "Языковые модели", "techEn": "Language models", "doesRu": "Автоматизация продаж, маркетинга и генерация продуктовых идей", "doesEn": "Automation of sales and marketing, and generation of product ideas", "resultsRu": "Источник цифр не приводит.", "resultsEn": "The source gives no figures.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2025, "yearEnd": 2025, "yearDisplay": "2025", "yearRaw": "2025", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Habr", "url": "https://habr.com/ru/articles/910880/" } ] }, { "id": 294, "catalogId": 302, "slug": "descartes-underwriting-294", "url": "https://vinumexmachina.com/casebook/cases/#case-294", "nameRu": "Descartes Underwriting", "nameEn": "Descartes Underwriting", "operatorRu": "Виноградари; мировой лидер по коньяку (не назван)", "operatorEn": "Grape growers; a world leader in cognac (not named)", "countryRu": "Франция, Австралия", "countryEn": "France, Australia", "domain": "business", "tech": "disease-weather", "stage": "commercial", "country": [ "fr", "au" ], "confidence": "c", "aiKind": "yes", "techRu": "Параметрическое страхование от заморозка и града: ИИ переобрабатывает исторические спутниковые снимки облачности плюс IoT-метеостанции", "techEn": "Parametric insurance against frost and hail: AI reprocesses historical satellite cloud imagery, plus IoT weather stations", "doesRu": "Выплата по факту наступления погодного события, без оценки ущерба на месте", "doesEn": "Payout on the occurrence of a weather event, with no on-site loss assessment", "resultsRu": "Конкретных цифр компания не публикует. Подтверждены только линейка параметрического страхования для виноградарства и ИИ в моделировании градового риска.", "resultsEn": "The company publishes no specific figures. All that is confirmed is a parametric insurance line for viticulture and AI in hail-risk modelling.", "caveatRu": "Источник — страницы самой компании; независимого подтверждения нет.", "caveatEn": "The source is the company's own pages; there is no independent confirmation.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2018, "yearEnd": 2025, "yearDisplay": "2018–2025", "yearRaw": "2018–2025", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Descartes Underwriting", "url": "https://descartesunderwriting.com/newsroom/descartes-insurance-australia-launches-parametric-frost-cover" } ] }, { "id": 295, "catalogId": 303, "slug": "hillebrand-gori-dhl-group-295", "url": "https://vinumexmachina.com/casebook/cases/#case-295", "nameRu": "Hillebrand Gori (DHL Group)", "nameEn": "Hillebrand Gori (DHL Group)", "operatorRu": "Импортёры и экспортёры вина на платформе myHillebrandGori", "operatorEn": "Wine importers and exporters on the myHillebrandGori platform", "countryRu": "Весь мир", "countryEn": "International", "domain": "business", "tech": "optimisation", "stage": "research", "country": [ "international" ], "confidence": "b", "aiKind": "yes", "techRu": "Прогнозирование спроса и моделирование погодных рисков", "techEn": "Demand forecasting and weather-risk modelling", "doesRu": "Совмещает метеоданные ВМО с базой маршрутов, предсказывая температурный и влажностный риск для конкретной отгрузки вина", "doesEn": "Combines WMO weather data with a route database, predicting temperature and humidity risk for a specific wine shipment", "resultsRu": "База из 110 000 морских маршрутов, 3 300 альтернативных маршрутизаций и 2 500 городов", "resultsEn": "A database of 110,000 sea routes, 3,300 alternative routings and 2,500 cities", "caveatRu": "Компания описывает базу как агрегацию метеоданных и логистики, а ИИ-функции упоминает в будущем времени.", "caveatEn": "The company describes the database as an aggregation of weather and logistics data, and mentions AI features in the future tense.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2023, "yearEnd": 2025, "yearDisplay": "2023–2025", "yearRaw": "2023–2025", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Hillebrand Gori", "url": "https://www.hillebrandgori.com/media/publication/tech-in-logistics" } ] }, { "id": 296, "catalogId": 304, "slug": "ivdp-winalytics-data-296", "url": "https://vinumexmachina.com/casebook/cases/#case-296", "nameRu": "IVDP «Winalytics» (Data+)", "nameEn": "IVDP “Winalytics” (Data+)", "operatorRu": "Институт вин Дору и Порту — регулятор наименования", "operatorEn": "Douro and Port Wine Institute — the appellation regulator", "countryRu": "Португалия", "countryEn": "Portugal", "domain": "business", "tech": "optimisation", "stage": "pilot", "country": [ "pt" ], "confidence": "b", "aiKind": "yes", "techRu": "Описательная, предиктивная и прескриптивная аналитика", "techEn": "Descriptive, predictive and prescriptive analytics", "doesRu": "Прогноз объёмов производства, предсказание себестоимости, оптимизация маршрутов дистрибуции, рыночные рекомендации и прослеживаемость от ягоды до бутылки", "doesEn": "Production-volume forecasting, production-cost prediction, optimisation of distribution routes, market recommendations and traceability from berry to bottle", "resultsRu": "Бюджет €300 000, программа SAMA IA в рамках Portugal 2020, проект завершён в декабре 2021.", "resultsEn": "A budget of €300,000, the SAMA IA programme under Portugal 2020, project completed in December 2021.", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2020, "yearEnd": 2021, "yearDisplay": "2020–2021", "yearRaw": "2020–2021", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Grande Consumo", "url": "https://grandeconsumo.com/ivdp-e-nova-ims-usam-inteligencia-artificial-para-otimizar-comercializacao-dos-vinhos-do-douro-e-porto/" } ] }, { "id": 297, "catalogId": 305, "slug": "plant-voice-297", "url": "https://vinumexmachina.com/casebook/cases/#case-297", "nameRu": "Plant Voice", "nameEn": "Plant Voice", "operatorRu": "Винодельни через акселератор Wine Tech Challenge", "operatorEn": "Wineries through the Wine Tech Challenge accelerator", "countryRu": "Италия", "countryEn": "Italy", "domain": "viticulture", "tech": "sensors-iot", "stage": "pilot", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "IoT-биосенсоры, имплантируемые в штамб лозы, плюс аналитика сокодвижения", "techEn": "IoT biosensors implanted in the vine trunk, plus sap-flow analytics", "doesRu": "Выявление водного стресса и болезни до появления видимых симптомов", "doesEn": "Detection of water stress and disease before visible symptoms appear", "resultsRu": "Один из восьми финалистов Wine Tech Challenge 2026", "resultsEn": "One of eight finalists in the Wine Tech Challenge 2026", "caveatRu": "В источнике нет ни машинного обучения, ни предсказательной модели — описана сенсорная технология.", "caveatEn": "The source has neither machine learning nor a predictive model — it describes a sensor technology.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Vinetur", "url": "https://www.vinetur.com/en/20260515100761/eight-startups-join-wine-tech-challenge.html" } ] }, { "id": 298, "catalogId": 306, "slug": "dolia-298", "url": "https://vinumexmachina.com/casebook/cases/#case-298", "nameRu": "Dolia", "nameEn": "Dolia", "operatorRu": "Винные компании", "operatorEn": "Wine companies", "countryRu": "Италия", "countryEn": "Italy", "domain": "business", "tech": "optimisation", "stage": "pilot", "country": [ "it" ], "confidence": "b", "aiKind": "yes", "techRu": "ИИ-централизация процессов продаж", "techEn": "AI centralisation of sales processes", "doesRu": "Автоматизация заказов и мониторинг остатков в реальном времени", "doesEn": "Order automation and real-time stock monitoring", "resultsRu": "Один из восьми финалистов Wine Tech Challenge 2026", "resultsEn": "One of eight finalists in the Wine Tech Challenge 2026", "caveatRu": "", "caveatEn": "", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "2026", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Vinetur", "url": "https://www.vinetur.com/en/20260515100761/eight-startups-join-wine-tech-challenge.html" } ] }, { "id": 299, "catalogId": 307, "slug": "vinobuzz-299", "url": "https://vinumexmachina.com/casebook/cases/#case-299", "nameRu": "VinoBuzz", "nameEn": "VinoBuzz", "operatorRu": "Потребительский маркетплейс", "operatorEn": "A consumer marketplace", "countryRu": "Китай (Гонконг)", "countryEn": "China (Hong Kong)", "domain": "business", "tech": "llm", "stage": "pilot", "country": [ "cn" ], "confidence": "c", "aiKind": "yes", "techRu": "Разговорный ИИ-сомелье поверх мультимерчант-маркетплейса", "techEn": "A conversational AI sommelier on top of a multi-merchant marketplace", "doesRu": "Подбор вина в диалоге с доставкой", "doesEn": "Wine selection in conversation, with delivery", "resultsRu": "Заявлено: оценка $10 млн, 1 000+ регистраций за две недели беты, 4 000+ SKU. Контекст рынка: менее 10% покупок вина в Гонконге совершается онлайн.", "resultsEn": "Claimed: a $10m valuation, 1,000+ sign-ups in two weeks of beta, 4,000+ SKUs. Market context: fewer than 10% of wine purchases in Hong Kong are made online.", "caveatRu": "Все цифры — из пресс-релиза компании, перепечатанного бортовым журналом; независимого подтверждения нет.", "caveatEn": "All the figures come from the company's press release, reprinted by an in-flight magazine; there is no independent confirmation.", "whyRu": "", "whyEn": "", "dataRu": "", "dataEn": "", "yearStart": 2026, "yearEnd": 2026, "yearDisplay": "2026", "yearRaw": "апрель 2026", "sectionKey": "G9", "sectionRu": "G9", "sources": [ { "name": "Champa Meuang Lao", "url": "https://champameuanglao.com/us10-million-tech-startup-vinobuzz-takes-the-traditional-wine-market-by-storm-as-hong-kongs-first-ai-agent-marketplace-for-wine/" } ] } ] }