Out2Eat

Inspiration

Deciding where to eat with a friend sounds simple until you have different tastes. I built Out2Eat to make that decision easier by finding restaurants that suit both people.

What it does

Out2Eat uses Qloo's taste intelligence to recommend restaurants based on two people's preferences, location, and budget. It presents a top match and alternatives, with explanations of why the recommendations may suit both people.

How I built it

I built Out2Eat as a web application using React, TypeScript, TanStack Start, Vite, and Tailwind CSS. I integrated Qloo's API for taste-based recommendations and used a server-side setup to keep the API key out of the client. I also worked on preference selection, recommendation evidence, and a responsive interface.

Challenges

One challenge was turning taste signals into useful restaurant recommendations for two people rather than optimizing for just one. I also had to troubleshoot API integration, improve how matches were explained, and test the experience across different screen sizes.

What I learned

Building Out2Eat taught me to connect an external taste-intelligence API to a practical user experience, validate recommendations against the needs of both users, and focus on a clear, working product rather than adding unnecessary features.