ToyoQuest

Inspiration

Toyota manufactures over 100 distinct variants of vehicles, which can make it overwhelming for customers to choose the right one. We wanted to make it easier (and faster) for users to figure out which Toyota fits their lifestyle the best. Instead of spending hours comparing different types of cars, ToyoQuest helps you find the best car meant for you.

What it does

ToyoQuest asks users 4 quick questions about their lifestyle to recommend the best Toyota vehicle for them! It's simple, clean, and less stressful than browsing through many car options online.

How we built it

We used TypeScript and Next.js for the frontend, Python and Flask for the backend, Firebase to create the database, and integrated Gemini and BeautifulSoup for data and AI.

Challenges we ran into

We ran into some challenges, such as figuring out how to connect Gemini, Firebase, and our frontend all together smoothly within a short period of time. Additionally, we had to figure out how to connect our backend and the frontend.

Accomplishments that we're proud of

Our UI turned out really super cute, we came up with a solution to the problem that was given, and it feels like something that Toyota could use one day. We're proud that we made something both functional and fun.

What we learned

We learned how to combine APIs like Gemini and BeautifulSoup, how to connect frontend and backend, and how much design really matters for user experience.

What's next for ToyoQuest

Next, we want to connect our ToyoQuest to real-time data and add more detailed information for each region and dealership. We would also like to include used cars, so that users can have more car options to choose from. Above that, by using a RAG model, the quizzes could give smarter, personalized suggestions for each user.