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Vivino and the Battle of the Rating Apps — Who Really Owns Wine Data?

⏱️ Reading time: 7 minutes

There’s something strange about pulling out your phone in front of a bottle of wine. A trivial gesture for sixty million users — and yet it raises a question few people put into words: who, ultimately, owns the opinion you’ve just left?

We’ve grown used to scanning labels, rating wines between two mouthfuls, following the recommendations of an algorithm that knows us better than our wine merchant. Vivino has slipped into our evenings with remarkable discretion, to the point of becoming an invisible infrastructure of taste. Behind that simplicity, however, lies a more complex reality: a silent battle for ownership of the world’s wine data. Who rates, who collects, who monetises, who decides? The question isn’t only economic. It touches on what we take to be expertise, trust, and the memory of wine.

A DANE WHO KNEW NOTHING ABOUT WINE BUILT THE WORLD’S LARGEST WINE DATABASE

The empire of the scan

Heini Zachariassen didn’t understand wine. A Faroese entrepreneur who came from cybersecurity, he often recounts that founding moment: finding himself lost in front of a supermarket shelf, unable to choose between one elegant label and another. “I didn’t know what to buy. There were only sophisticated labels and prices.” In 2010, with Theis Søndergaard, he co-founded Vivino in Copenhagen. The idea fits in one line: photograph a label to instantly get reviews from the community. A Shazam for wine.

The gesture that became universal: scanning before choosing.

Fourteen years later, the app boasts more than 60 million downloads, a database of 16 million wines catalogued, 200 million ratings and 1.5 billion label photos collected by its users. Vivino is today regarded as the largest online wine marketplace in the world — and the largest wine database ever built, fed free of charge by its own community. The company has raised more than $220 million in venture capital, including $155 million in a round led by the Swedish fund Kinnevik in 2021.

“No one else can do what we do, because no one else has access to the kind of data we own.”
Heini Zachariassen, founder of Vivino, at the opening of the first physical shop in Singapore, September 2024

YOU ARE THE USER, THE COMMUNITY — AND THE RAW MATERIAL

The question no one asks

© Unsplash — Behind every scanned label, a data point joins a proprietary database.

Every rating you leave, every bottle you scan, every preference you express: all of it feeds a proprietary database, owned by a private company, financed by venture capital. You are at once the customer, the contributor and the resource. This isn’t a criticism in itself — Wikipedia runs on a comparable model. But the essential difference is that Vivino monetises that contribution.

The recommendation algorithm, the “Match for You” feature that calculates your personal affinity with a wine based on your tasting history, the recently launched AI Sommelier — everything rests on the data users have generated without pay. In 2024, Vivino opened its first physical shop in Singapore, whose selection was built entirely from the behavioural data of its local users. As Zachariassen himself puts it: “No one else can do that.”

The question of data ownership becomes even sharper for winemakers. A producer can find themselves rated by thousands of users without having been consulted, with no access to those aggregated ratings, and with no lever to influence their score — other than persuading their buyers to download the app and leave a good review. On wineandtech.fr, we’ve already explored how blockchain can give traceability and power back to producers — participatory rating poses a symmetrical but opposite problem: here it’s the consumption data that slips away from those who make the wine.

“If a wine drops below 4 stars on Vivino, people no longer give it a chance. It doesn’t matter what your reference guide or your wine merchant says.”
A French importer, in Bordeaux trade circles

THE CROWD VERSUS THE EXPERT: A BATTLE REDRAWING AUTHORITY IN THE WINE WORLD

Two hundred million ratings against five recognised palates

Traditional wine criticism rests on an aristocratic model: a handful of palates trained over decades define what deserves to be drunk. Robert Parker, Wine Spectator, Jancis Robinson, Decanter — these institutions rate perhaps 20,000 to 30,000 wines a year. Vivino handles two million scans a day. The argument of scale is real. A Polish Riesling or an emerging English wine can rack up hundreds of ratings on Vivino before a specialist critic has ever gone near them.

© Unsplash — Professional tasting versus the verdict of the connected crowd.

But the system’s limits are just as real. A Vivino rating carries the same weight from the palate of a beginner who has only ever drunk sweet wines as from that of a seasoned enthusiast who has been tasting for twenty years. The algorithm favours immediately pleasing wines — round, accessible, generous with fruit — at the expense of wines built to age, often austere in their youth and revealing their greatness after ten years in the cellar. A Barolo or a Chablis premier cru will be mechanically penalised if opened too early. It’s a structural bias that the crowd, by its very nature, cannot correct.

VIVINO, CELLARTRACKER, WINE-SEARCHER: THREE PHILOSOPHIES OF DATA, THREE VISIONS OF WINE

The ecosystem of challengers

© Unsplash — Managing your cellar also means choosing who to entrust your data to.

CellarTracker, founded in 2003, is built on a radically different philosophy. Detailed technical notes, contributions from serious collectors, vintage sheets documented over decades — it’s the Wikipedia of wine, deep rather than broad. Its quasi-collaborative model keeps the data accessible to the community without monetising it in the same way. Wine-Searcher plays yet another tune: a global price engine, it covers nine million wines and their availability at thousands of merchants. The data here isn’t affective, it’s transactional.

Delectable, bought by critic Antonio Galloni’s Vinous group, bets on the quality of its notes rather than their quantity, with a community of recognised sommeliers and critics. In France, apps such as Wine Advisor (E.Leclerc) or Raisin (a natural-wine specialist) seek their niches from angles Vivino doesn’t cover. Each of these players aspires to become the infrastructure layer of the wine decision — but none yet has Vivino’s critical mass.

The advantage is self-reinforcing: the more users, the more precise the database; the more precise the database, the more users it attracts. It’s what platform economists call a data moat — a near-impassable moat of data. With 2 million daily scans, Vivino is fifty times bigger than its nearest competitor in this segment, according to Zachariassen himself.

THE ARTIFICIAL SOMMELIER WON’T REPLACE THE WINEMAKER — BUT IT HAS ALREADY CHANGED THE BUYER

AI moves into the cellar

Vivino recently launched its AI Sommelier — a conversational assistant that knows your scan history, your ratings, your preferences, and answers questions in natural language. It knows you’ve liked three Burgundy Pinot Noirs and that a heavily dosed Champagne doesn’t win you over. On the iPhone 16, integration with Apple Visual Intelligence even lets you scan a label directly via the Camera Control button, without opening the app — with Vivino’s data working in the background.

© Unsplash — The AI sommelier: your palate digitised, in the service of a proprietary algorithm.

This shift isn’t neutral. It means that the wine data you produce — your tastes, your purchases, your personal palate — is now a commercial asset of the first importance, refined in real time by artificial intelligence. In our article on drones and AI in viticulture, we explored how technology is transforming the production side of wine; Vivino is carrying out the same transformation on the consumption side, with the same instrument — data — but in very different hands.

Vivino has undeniably democratised access to information about wine. It has given a voice to millions of enthusiasts who didn’t have one, shone a light on regions ignored by the specialist press, and made choosing a bottle less intimidating. But by consolidating that information into a proprietary architecture, it has also centralised a power that was once diffuse: the power to decide what deserves to be drunk — and what doesn’t.

Do you use Vivino or another app to choose your wines? Do you still trust your own palate — or have you delegated that decision to your phone? Share your experience in the comments.

Sources: Wikipedia — Vivino · A+ Singapore — Interview with Heini Zachariassen (2024) · Locals Insider — Vivino App Review (2026) · The Drinks Business — Vivino and the future of wine retail · InVintory — Best Wine Apps 2026 · Petit Vin Entre Copains — Wine-rating apps compared · SommelierX — Alternatives to Vivino (2026)

September 10, 2026
The AI Sommelier: Can You Recommend the Right Wine Without a Palate?

⏱️ Reading time: 7 minutes

Thirty percent of French people say they have already consulted an artificial intelligence to choose a wine or a spirit. Among 18-to-25-year-olds, the figure climbs to 58%. That number, drawn from the latest SOWINE/Dynata barometer, marks a turning point: for the first time, the machine has officially invited itself into the French drinker’s purchase journey. We ask it for a pairing for tonight’s dinner, an opinion on a bottle received as a gift, an idea for breaking out of our habits. And it answers — quickly, politely, with disarming self-assurance.

One question, however, hangs in the air — one the surrounding enthusiasm carefully avoids: what, exactly, is that recommendation based on? When a sommelier advises you on a wine, they draw on years of tastings, of aromas, of memory. The AI, for its part, has never tasted anything. Can you really recommend the right wine without a palate?

THREE WAYS TO ADVISE ON A WINE WITHOUT HAVING DRUNK A DROP

Behind the “AI sommelier,” three engines

The most widespread recommendation engine doesn’t analyse the wine: it analyses the drinkers. This is collaborative filtering — Vivino’s method, borrowed from Netflix and Amazon. Its principle fits in a single sentence: people who liked the same wines as you also liked this one. The suggestion is born of a statistical correlation between millions of ratings, not of any understanding of the liquid. Effective at guessing what will please you, blind to what is actually in the glass.

A second family reasons about the wine itself — or rather about its technical sheet. Apps such as WineRing or the iAlacarte sommelier match an aromatic profile (tannic structure, acidity, residual sugar, intensity) against that of a dish (cooking method, sauce, garnish). It’s the classic logic of food-and-wine pairing, encoded in a database. Finer than collaborative filtering, it still depends on descriptors entered, upstream, by humans.

The third family, the most recent and the most spectacular, rests on large language models. Queried in natural language — “I’ve got a duck breast with cherries and three bottles in my cellar, what would you suggest?” — the model produces a reasoned, often startling answer. But all it does is reassemble, on the fly, what thousands of tasters have written on the web. It compiles; it does not experiment.

These three approaches share one blind spot. None of them tastes. They predict from proxies — co-occurrences of ratings, sheets of descriptors, scraped text. Wine, as a sensory object, remains strictly inaccessible to them. And that is precisely where the science of the palate becomes illuminating.

THE PALATE ISN’T IN THE MOUTH — IT’S IN THE BRAIN

What brain imaging reveals about the sommelier

In 2005, a team published in NeuroImage the first functional magnetic resonance imaging study devoted to sommeliers. Seven experts, seven novices, the same wine. The result: in the experts, tasting activates a particular network — the left insula and the orbitofrontal cortex, two regions dedicated to integrating taste and smell. The researchers’ conclusion is counter-intuitive: that difference reflects not finer taste buds, but a learned ability to connect sensations to memory.

The studies that followed confirm and refine this. In 2014, a Besançon team (Pazart et al.) showed that the expert reacts more immediately and more “economically” than the novice, drawing heavily on memory structures — the hippocampus, the temporal pole. Where the beginner gropes through diffuse associative areas, the professional evaluates the wine and recognises its type in a single movement. In 2016, a study of Master Sommeliers observed a reinforced memory network; in 2024, researchers at the Basque Center on Cognition measured, in sommeliers, more intact white matter in the tracts linking perception, memory and language. Training, quite literally, reshapes the brain.

Taste isn’t on the plate; it is built inside our heads.
Gabriel Lepousez, neurobiologist at the Institut Pasteur

For this specialist in sensory perception, tasting is an operation of formidable complexity: the brain must rank information arriving through the eyes, through the nose (directly and by retronasal olfaction), through the mouth and through touch, synthesise it, compare it against memory, then translate it into words. One detail illuminates all the rest: sight alone occupies 15 to 17% of the cortex, against barely 1% for smell. Faced with uncertainty between an odour and a colour, the brain almost always rules in favour of what it sees.

The human expert, fallible by design

This primacy of the brain has a flip side: it makes perception manipulable. The most famous experiment is that of Frédéric Brochet, Gil Morrot and Denis Dubourdieu, conducted in Bordeaux in 2001. Fifty-four oenology students were given a white wine to taste, then the same white wine dyed red with a neutral colourant. The verdict: the students described the second using the vocabulary of red wines — black fruit, tannins — as if the colour had rewritten their sense of smell.

A second experiment by the same researcher is just as cruel: a single Bordeaux, presented two weeks apart under the label “table wine” and then “grand cru,” drew radically opposite judgements. In other words, even the most seasoned taster remains subject to expectation, context and price. Their strength — a brain that integrates everything — is also their weakness.

SOMMELLERIE: AUGMENTED OR REPLACED?

What the machine gets right — genuinely

Against this backdrop, the AI has real strengths it would be dishonest to brush aside. First, it democratises: a sommelier’s advice is expensive and intimidating; an assistant available around the clock, free in its basic versions, lifts that barrier. Next, on everyday food-and-wine pairing, reasoning by aromatic profile is solid — it applies, without faltering, principles the average drinker doesn’t know. Finally, in a twist of irony, the AI escapes Brochet’s traps: neither colour, nor label, nor price throws off a machine that sees nothing. But that is precisely because it perceives nothing at all.

What it will not do

For that is where its competence ends. The AI will not taste the bottle opened in front of you: it cannot tell you that it’s corked, that it cooked in a car boot over the summer, that it’s going through a dumb phase. It reasons about an abstract, average, statistical wine — never about the real wine in the glass. It doesn’t read the table, doesn’t sense that a guest would rather avoid red or that the mood calls instead for something sparkling. And when it promises to choose a wine “to match your mood,” that is where it is most helpless: pairing to a dish can be encoded; pairing to a state of mind remains, for now, pure marketing.

A librarian, not a taster

Perhaps we’re simply reaching for the wrong metaphor. The AI sommelier is not a sommelier: it is a librarian of wine, prodigious at retrieving, cross-referencing and serving up information scattered across millions of bottles and reviews. On that ground — “what is a Crozes-Hermitage?”, “is this Pomerol any good?”, “which red with an osso buco?” — it renders a real and democratic service. But recommending the right wine remains, in an irreducible part, an act of embodied sensory memory that the machine cannot perform. The SOWINE barometer puts it in its own way: AI enters the picture not as a substitute, but as a new tool for guidance. The palate, meanwhile, stays between the two ears.

Would you trust an AI to choose the wine for your next dinner — or do you keep the final word? Tell us in the comments, and find our by-the-glass tastings on Instagram @wineandtech.

Sources: SOWINE/Dynata Barometer 2026 · Castriota-Scanderbeg et al., NeuroImage, 2005 · Pazart et al., Frontiers in Behavioral Neuroscience, 2014 · Banks et al., Frontiers in Human Neuroscience, 2016 · Basque Center on Cognition, Human Brain Mapping, 2024 · Morrot, Brochet & Dubourdieu, “The Color of Odors,” Brain and Language, 2001 · Gabriel Lepousez, Institut Pasteur (interviews in Le Figaro and Le Rouge & Le Blanc).

September 5, 2026