Car recommendation software

The product is supposed to prompt the user for data and recommend 3 cars with the determined filters. I percent match is shown to the customer to show how much of a good recommendation it is to them.

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Inspiration

The matador Ai challenge. A personal need for a car suggestion system.

What it does

The software will recommend 3 cars to a user after asking a series of questions. It will have a match percentage which allows the user to see whats the best car for the user.

How we built it

We wrote the backend for the chatbot and the comparison page simultaneously with the frontend. Then we integrated together using RESTApis

Challenges we ran into

The integration between the frontend and backend caused us the most issues

Accomplishments that we're proud of

The chatbot answers questions that are off topic and redirects the user to the important question. The Ui is very pretty. The backend works great

What we learned

Using OpenAi api, RESTAPIs, flutter, extensive python use.

What's next for Car recommendation software

We hope to attend many more hackathons and continuously grow our skills

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