
What happened
Circlia started a proof-of-concept for TASTE SIGNAL: visitors to Holland Village Cafe FUKUOKA taste cookies and rate them on five axes — sweetness, saltiness, texture, aroma, and aftertaste — plus a four-level answer on whether they would pay again. The data is compared between high- and low-repeat-intent groups, and a generative AI then suggests a direction for the next recipe trial.
Why it matters
Circlia argues that storing the whole cycle — tasting, sensory evaluation, purchase intent, recipe changes, and re-evaluation — builds a data asset, and that tracking how purchase intent shifts when a recipe changes is what could make the platform unlike others.
WHO IT HITSFood and cosmetics product developers may gain a new source of evidence for deciding recipe changes, and research institutions working with Circlia could get access to accumulated sensory evaluation data.
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Circlia's TASTE SIGNAL effort is built around a simple loop: taste, evaluate, state purchase intent, change the recipe, and evaluate again. At this stage, the body says the AI is at the point of putting hypotheses into words based on the real data that has been accumulated.
What Circlia is betting on is not any single evaluation, but the changes themselves — specifically, how purchase intent moves when a recipe is altered. Those changes, accumulated over time, are what the company describes as a data asset and as the basis for a platform it says would be unlike others.
The immediate test bed is a cookie product sold through Circlia's own store and e-commerce. The 100 pre-launch cans sold out the same day, and after a data-collection period, reopened reservations already had customers waiting in line.
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