n1

Inspiration

Dating apps often focus on surface-level interests or mutual swipes, leaving users wondering why they matched. We wanted to reimagine connection by revealing the cultural threads that weave people together—music tastes, cinematic obsessions, thematic fascinations. n1 dives deeper, blending psychology, media preferences, and taste mapping to make matches feel intentional and insightful.

What it does

n1 is a dating app that gives users Deeper Insights, Not Just Matches. When users match, the app doesn’t just say “You matched!” — it adds context: “You both share a taste for dystopian themes, synthwave music, and a love for Blade Runner.” This transforms a swipe into something meaningful. Beyond matches, the Taste Explorer enables users to discover cultural affinities and their own taste profile—even if it doesn’t lead to a direct connection. It’s a space for self-awareness, exploration, and discovery. Our Why We Match engine explains compatibility using nuanced keywords, moving well beyond basic interest tags. The system mimics Qloo’s philosophy by simulating deep, tailored recommendations and connections across categories.

How we built it

• Frontend: Crafted in React for responsive UI and real-time interactions
• Backend: Powered by Express.js, with dynamic routing and modular APIs
• Taste Compatibility Logic: Custom-built getTasteCompatibility algorithm analyzes semantic overlaps and thematic affinities
• AI Integration: Leveraged taste-based recommendation models to simulate cultural mapping
• Data Simulation: Extended metadata model to reflect user affinities across genres, moods, and styles

Challenges we ran into

• Uploading and storing picture URLs reliably across environments
• Smoothly integrating AI services to enhance user insights without slowing performance
• Building a flexible taste taxonomy that remains meaningful but lightweight
• Mapping non-obvious compatibility triggers while avoiding bias or overfittin

Accomplishments that we're proud of

• Successfully implemented AI-powered compatibility scoring
• Developed an intuitive "Why We Match" explanation framework
• Built a functioning Taste Explorer prototype with category-spanning recommendations
• Created a seamless, modern UI and API that opens doors for further personalization

What we learned

• Taste is more than preference—it’s a window into identity
• Compatibility isn't binary; it thrives on nuance, shared experiences, and emotional resonance
• Building meaningful recommendations requires both technical precision and creative empathy
• AI can enhance intimacy and insight when used responsibly and artfully

What's next for n1

• Incorporating real user data to refine and validate taste mappings
• Expanding taste categories to include literature, cuisine, art, and more
• Enhancing visual insights with AI-generated summaries of shared interests
• Launching a beta test to gauge emotional impact and refine UX
• Exploring ethical frameworks for taste-based matchmaking algorithms

Built With

• express.js
• openai
• qloo-ai
• react
• supabase
• tailwind-css
• typescipt