Palate
Mobile app with a taste model learned from behaviour, location aware search, a social layer, and recommendations that work from the first open.
Palate was a founding team with a strong product thesis about how people actually choose where to eat, and nothing built yet. The product had to be good enough that users would open it repeatedly, in a category where the incumbents are very large.
Taste model from behaviour
Scrolling reveals more than a questionnaire
Useful from the first open
Cold start was the thing we had to solve
Location-aware search
Instant on a mobile connection
Social layer
Friends + taste-matched strangers worth following
Measurement built in
Product team sees which strategies win
We built the mobile application and the services behind it.
A taste model that learns from what users actually do, not from a questionnaire they abandon. Recommendations that work from the first open. The cold start problem is what kills discovery apps, so Palate's version was engineered to earn its first useful result on install.
Location-aware search fast enough to feel instant on mobile. A social layer that surfaces friends and taste-matched strangers worth following. Measurement built in throughout, so the product team can see which strategies drive return visits and tune without an engineer.
Two to three engineers from MVP through launch and into ongoing support.
A shipped Palate app with a recommendation system the team can tune from real usage without an engineer.
Capabilities used
Tell us about it. We'll tell you honestly whether we're the right team to help ship it.