When someone enters a new review, Gastrograph compares the report with the app’s body of data. Its AI analysis can then determine the flavors in the food even better than the person who submitted the review, according to Jason Cohen, the founder and CEO of Analytical Flavor Systems (AFS), the company behind the app. Humans are constantly experiencing flavors that we can’t identify, Cohen says: “We’ve all had that feeling: Oh, I know this flavor, what is that?”

Moreover, we don’t consciously notice many flavors we perceive, even though they can be important components in a gustatory experience. As an example, Cohen says that if you add trace amounts of vanilla to milk, people generally report that it tastes sweet, creamy, and delicious, without putting their fingers on vanilla. If someone tries lychee for the first time and reports only different flavors they’re familiar with, the app may be able to recognize that they’re really tasting lychee, Cohen says.

In each food and drink sampled, Gastrograph tries to make a comprehensive model by pinning down all of its flavors, including the hidden ones. The app is “literally reading someone’s mind,” Cohen says, but then quickly corrects himself. “No, if we were reading their mind, they would’ve known they were tasting it. We’re reading their subconscious.”

AFS is selling Gastrograph as a way for food manufacturers to get a better understanding of what they’re producing and how it relates to customers. Some of the company’s first clients were brewers who wanted to make sure their beers maintained the same flavor over time. Brewing depends on agricultural products that naturally vary from year to year, which chafes against the brewer’s need for consistency.

Yards Brewing in Philadelphia, AFS’s longest-running customer, uses the tool routinely. “We just register a user and they sit down with a bartender, get out their phone, and have a tasting. By doing that repeatedly, we can calibrate them as a taster,” says Frank Winslow, Yards Brewing’s director of quality control. Since the app knows what the beer should taste like at each stage, tasters can be used to check that the product is on track. “Having those kinds of warnings early in the process is a huge step,” Winslow says.

Once Gastrograph models a food or drink, it can then try to simulate what would happen when you change that food or drink’s flavor or introduce it to new demographics. The app does this using a technique from the field of computational linguistics. Language researchers use machine learning to analyze huge piles of text and create many-dimensional models of the meanings of words. The models can also find relationships between words using operations such as “king − man + woman = queen.” Gastrograph uses similar operations in its flavor space to try to predict how new demographics will like foods they haven’t tried.