Streamline Travel

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Inspiration

When reflecting on our struggles as students, we recognized how challenging it has been for us to decide how to get home with many different websites and conflicting values of cost, dates, and travel duration. This fragmented experience makes it difficult to quickly find the best route and adds stress to our daily lives. We were inspired to build Streamline, a unified platform that brings all of these options together in one place and helps users make smarter, faster travel decisions. Streamline also allows users to combine airlines or travel methods to create even more effective solutions.

Learning Experiences

This hackathon pushed us to work with new technologies and external APIs that we had never experienced before. We gained experience integrating groq, building a chatbot with voice-to-text capabilities using Deepgram. Our team also learned how to separate the backend and frontend into different host services and handle the connection. We also purchased and set up a special domain for the site. We also learned how to balance feature ambition with feasibility, prioritizing core functionality while maintaining a clean and intuitive user experience.

Building the Project

We designed Streamline as a multi-transport travel comparison platform that aggregates data from flights, trains, and buses into a single interface. The frontend was built with React and TailwindCSS to ensure a responsive and user-friendly experience, while the backend uses Node.js to handle search requests, recommendations, and API orchestration. Travel data is stored and processed using MongoDB, allowing us to efficiently compare prices and travel times. To enhance usability, we integrated an AI-powered chatbot using the groq API, enabling users to ask natural language questions such as “What’s the cheapest way to get there?” or “What’s the fastest option available?” We implemented speech-to-text using Deepgram. We also implemented smart recommendation logic to highlight the best value, fastest, and cheapest travel options, helping users make informed decisions at a glance.

Challenges

One of our biggest challenges was scraping data from multiple travel sources and combining it to create connected travel methods. Working with a frontend and backend that is separated by host slowed development. Additionally, integrating the chatbot with real travel data in a meaningful way required iteration and refinement. Despite these challenges, our team collaborated closely, divided responsibilities effectively, and adapted quickly, allowing us to deliver a platform that we can be proud of.