Inspiration We wanted to create a travel planner that feels deeply personal. Instead of generic suggestions, what if your taste in music, books, and movies could unlock travel recommendations that truly resonate with you?
What it does TasteTrails uses your cultural preferences—like favorite bands, books, brands, and films—to generate personalized travel destination recommendations that align with your personality and taste.
How we built it We used Next.js, TypeScript, MongoDB (via Prisma), and Qloo API to match user input to cultural profiles and suggest destinations. Authentication is handled via better-auth, and the app uses serverless API routes for processing preferences and delivering results.
Challenges we ran into Understanding and integrating the Qloo API effectively.
Mapping abstract taste data into meaningful travel suggestions.
Debugging route handlers and ensuring type safety across the stack.
Accomplishments that we're proud of Built a fully working taste-to-travel pipeline with real cultural analysis.
Clean and interactive frontend that’s easy for users to use.
Achieved recommendation logic that actually feels personal and unique.
What we learned How to build API-driven personalization features with real user taste data.
Working with external APIs and interpreting their results.
Fine-tuning backend logic for meaningful output using minimal input.
What's next for TasteTrails – Smart Taste-to-Trip Add richer destination data (photos, guides, local experiences).
Improve taste analysis using more user signals and deeper profiling.
Let users save and share their cultural travel personas.
Built With
- mongodb
- nextjs
- typescript
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