Travel Buddy

Inspiration

With spring break just behind us and summer fast approaching, we all shared a common struggle—wanting to explore new places but feeling overwhelmed by the planning process. It’s something we hear people talk about all the time. You may have even heard, “I don’t have time to plan a trip!” That’s where Travel Buddy comes in. Now, with just a few clicks, anyone can plan a trip in minutes.

What it does

Travel Buddy is an AI-powered travel planning app designed to take the stress out of organizing your next adventure. Instead of spending hours researching destinations, accommodations, and activities, Travel Buddy streamlines the process by asking you a series of thoughtful questions.

Based on your responses, our AI curates a personalized itinerary that aligns with your unique preferences. Your itinerary includes a day-by-day breakdown of activities tailored to your interests, flight details with arrival and departure times, recommended hotel stays with cost estimates, and handpicked experiences and attractions to create unforgettable memories.

With Travel Buddy, planning your dream trip is effortless—so you can focus on enjoying the journey.

How we built it

We kicked off our project with a clan of whiteboards, brainstorming and refining our ideas. Many concepts came and went, but after several iterations, we gathered enough information to move forward. We chose our tech stack, designed rough page layouts, and mapped out data flows before diving into development. Our stack included:

Python & Django for backend development
HTML, CSS, and JavaScript for the frontend
AWS EC2 for deployment
OpenAI for AI-powered recommendations We tackled development page by page, refining the experience as we went. Along the way, we continuously updated our CSS file to improve the look and feel of the platform.

Challenges we ran into

Building Travel Buddy in just 24 hours was no small feat. Some of the biggest hurdles we encountered included:

EC2 Deployment Issues – Setting up our AWS instance didn’t go as smoothly as expected.
LLM Model Availability – The model we planned to use wasn’t accessible as expected, requiring us to pivot.
Time Constraints – With only a day to build the project, we had to optimize every minute and make tough prioritization decisions.

Accomplishments that we're proud of

We did not let issues with onboarding the hackathon platform block us from moving forward. We were able to pave our own way.
We were able to delegate tasks effectively ensuring that no team member is idle or blocked for too long.

What we learned

This experience taught us the importance of adaptability and teamwork. We learned to quickly troubleshoot issues, pivot when needed, and manage our time effectively under pressure.