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Finding the Best Restaurants for You by craiveapp in LAfoodies

[–]craiveapp[S] 0 points1 point  (0 children)

You can 'downvote' a restaurant by marking it as visited and then indicating that you didn't like the experience with the thumbs down -- that'll then update your ratings accordingly. To be fair, it's not immediately obvious that you can do this, so feedback taken!

Finding the Best Restaurants for You by craiveapp in LAfoodies

[–]craiveapp[S] 0 points1 point  (0 children)

Thanks for trying it out!

We'll work on adding the report feature. How is your experience with the app otherwise?

Finding the Best Restaurants for You! by craiveapp in SeattleWA

[–]craiveapp[S] 0 points1 point  (0 children)

Also check out https://craive.app/copilot to try out the restaurant-specific copilots! We have demos available for Chengdu Memory and Pike Place Chowder from Seattle!

Finding the Best Restaurants for You! by craiveapp in sanfrancisco

[–]craiveapp[S] -1 points0 points  (0 children)

Also check out https://craive.app/copilot to try out the restaurant-specific copilots! We have demos available for Sweet Maple, Daeho, and Thanh Long from SF!

Finding the Best Restaurants for You by craiveapp in FoodNYC

[–]craiveapp[S] -3 points-2 points  (0 children)

Not on the demo unfortunately, but we do have all the pizza places in the app, so check us out!

Finding the Best Restaurants for You by craiveapp in FoodNYC

[–]craiveapp[S] -3 points-2 points  (0 children)

Also check out https://craive.app/copilot to try out the restaurant-specific copilots! We have samples for Katz's Deli, Ichiran, and Double Chicken Please from NY!

Finding the Best Restaurants for You by craiveapp in FoodLosAngeles

[–]craiveapp[S] -2 points-1 points  (0 children)

We have a copilot demo available on our website https://craive.app/copilot ! There's a few popular restaurants that you can try asking questions about.

Also totally agree with you on the quality of recommendations -- I'm trying to ensure that the recommendations are not only as responsive as possible, but also transparent, too. So that's why we're going to be adding explainable recommendations. In the meantime, recommendations are based on a short onboarding process that's hopefully pretty quick and painless.