MicroItinerary — AI Travel Planner

Problem

Travel apps optimize for proximity and ratings. They don't consider human energy levels, group dynamics, or intelligent budget allocation.

Business Impact

Trip planning is tedious and error-prone. Most apps just list options — they don't understand your constraints. This uses AI to actually solve the planning problem.

System Approach

• Spring Boot 3.2.2 + Java 21 backend with Flyway migrations
• React 18 + Vite PWA frontend with offline support via IndexedDB
• OpenAI GPT-4 integration for intelligent destination and cost suggestions
• Redis caching to reduce API costs and improve response times
• Google OAuth 2.0 + JWT for secure authentication

Key Decisions & Trade-offs

• PWA over native app — broader reach, single codebase, works offline
• OpenAI API adds latency and cost, but rule-based alternatives lack quality
• Expense splitting algorithm prioritizes simplicity over Splitwise feature-parity
• PostgreSQL 16 for relational data with potential for vector search later

Current Status

Backend API functional. Frontend PWA with offline sync working. AI suggestions integrated.

Roadmap

• Add calendar view for annual planning
• Implement real-time expense tracking
• Add collaborative trip editing

What I'd Improve Next

• Could add caching layer for repeated AI queries
• Consider fine-tuning a smaller model for cost estimation

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