TravelBro

Inspiration

Planning a trip usually means opening multiple tabs, checking maps, reading blogs, and trying to organize everything manually. We wanted to simplify that process by creating an AI-powered travel planner that helps users both discover places and automatically structure their trips. Our goal was to combine open-ended exploration with organized itinerary planning in one platform.

What it does

Travel Planner is an AI itinerary planning tool with two main modes: Suggestion Mode and Planner Mode. In Suggestion Mode, users enter a general location and the system generates travel suggestions based on that area. In Planner Mode, users specify a location and the AI automatically adds recommended destinations into a structured itinerary. The app also features a 2D projection of Earth where each location is represented with pins that users can click on to view more details.

How we built it

The project started as a simple TypeScript UI template, but as a team we worked through the design process together and used Claude Code to help bring our ideas to life. We integrated AI-based suggestion logic, itinerary structuring, a map visualization layer, API calls for travel data, while refining the UI to make sure it was both functional and easy to use.

Challenges we ran into

We faced challenges in structuring AI outputs into usable itinerary formats and making sure the suggestions were relevant without being too generic. Integrating map visualization with dynamically generated data was also difficult. Managing asynchronous API calls, designing a UI that looked good while still presenting a lot of information were all problems we had to solve within a short timeframe.

Accomplishments that we're proud of

We’re proud that we were able to successfully implement AI-driven itinerary generation and create two separate planning workflows. We also built prompt-handling logic that determines whether a user’s input should be treated as a suggestion request or a structured planning request based on the format of the prompt. In addition, we integrated real-time API calls, built a functional map-based visualization system and designed a UI that is both visually appealing and usable, all within the hackathon timeline.

What we learned

We learned how to turn natural language AI outputs into structured application logic and how important UI and UX are when presenting generated content. We also gained experience working with asynchronous data pipelines, managing API integrations, and designing systems that connect AI suggestions with geographic visualization.

What's next for Travel Planner

In the future, we could expand personalization based on user preferences, support multi-day trip optimization, allow collaborative trip planning, and integrate real-time updates like weather or availability. We also plan to enhance the map with route planning and develop a feedback system to improve AI suggestions over time.