WayHome

Inspiration

Trying to find housing is annoying, especially if you're not from the area you're looking to move to

What it does

Allows you to build out "route maps" for homes which fit your liking. Search for homes based on distance to an anchor point, then also compare average commute times across amenities like gyms, restaurants, and much more. On top of this, user can build home profiles to easily compare multiple options. This makes finding a new living situation much less of a headache!

How we built it

Built using Next.js and TypeScript, powered by Replier, Google Maps, and Gemini. The backend uses a combination of Gemini and Google Maps to search for, locate, and pinpoint amenities while using Replier for home searching.

Challenges we ran into

Data, data, data. Finding accurate addresses, cost of living, and other live data is expensive and was challenging for the scope of our project. We were able to make a solid product relying on publicly available data, but our next steps would definitely be to get more data!

Accomplishments that we're proud of

We were able to successfully craft our vision of a good home finder tool, allowing users to cross compare homes.

What we learned

Home data is very expensive

What's next for WayHome

Upgrading our data pipeline to include accurate cost of living and more intricate pricing, as well as upgrading the models and methods for amenity searching.

Built With

• ai
• flask
• geminiapi
• python
• railway
• react
• typescript