TravEat is a globally-targeted hybrid mobile application that collects and analyzes regional food culture data, enabling users to explore local ingredients, recipes, and nutritional insights through AI—even while traveling. The app also supports direct shopping experiences and offers GPT-powered recommendations tailored to dietary needs and location context.
Key Features
Exploration of regional food culture through a 3D global map interface
AI-driven analysis of popular ingredients and local recipes per region
GPT integration for contextual food recommendations and nutritional analysis
Multilingual food descriptions and integrated shopping experience
Personalized dietary suggestions based on user location and health profile
Key Metrics
Food culture datasets collected and processed from over 100 countries
Internal AI recommendation accuracy rate of 83.2%
Continuous UX refinement based on international user feedback
Tech Stack
Frontend: Flutter
Backend: Node.js, MySQL
AI/LLM: GPT-4 API, Embedding-based search and classification
GIS: 3D global map
Translation: Google Cloud Translate API
Data Collection: Hybrid method using web scraping and manually curated CSV datasets
Contributions & Role
Led end-to-end product planning and UI/UX architecture
Developed the global food culture data ingestion and cleaning pipeline
Built the GPT-based prototype for food analysis and recommendation
Designed scalable Flutter UI components with multilingual support
Integrated 3D map visualization with ingredient metadata for interactive exploration