Creating a recommendation platform which learns your preferences and serves up new choices each time you order.
An app which allows you to use two options for serving up new food options depending on how much you choose to opt in: a local option that stays on your device, and one that leverages AI and crowdsourcing to find more refined recommendations.
A preview to the playful nature of the platform and to highlight the backend AI from IBM Watson.
Instead of opting for traditional forms, the flow is meant to be more conversational and inviting. There's a lot of information asked at the beginning to serve the best results and we wanted it to be as engaging as possible.
Swipe left or right
Using existing interaction models from dating apps, the user would swipe left and right and decide what existing restaurants in the area they like and don't like. This can be saved locally on the device, or the user can opt-in to sharing this data with the Food Fight platform to serve up more precise recommendations.
After a couple swipes, the app would then recommend a restaurant to the user. This will include things like user rating, and options find the restaurant, call to order and look at the menu to see what's available.
Since this app concept has been created, there have been great leaps in machine learning and AI that I'd love to explore and integrate into the experience.
Additionally research would be necessary to see if there is a way to integrate into delivery apps and have a more seamless end to end experience.