Inspiration
We wanted to build this product because we needed a simple way to understand and manage our finances without having to use a confusing and overwhelming personal finance apps like Mint. We wanted a simple solution that interacted with us like a real financial assistant would, chat based.
What it does
The product allows users to connect their financial data and chat with our AI personal finance assistant to better understand their current financial situation and navigate specific issues such as how to decrease spending or plan their budget. It also suggests offers from our partnered businesses that allows users to potentially save on services such as insurance, banking, energy or investing based on their financial data.
How we built it
We built the frontend using react + vite and we built the backend using express. We use supabase for the database and groq API.
Challenges we ran into
Our main challenge was connecting the ai in the backend to frontend.
Accomplishments that we're proud of
We are proud of finishing an AI Personal finance MVP in 3 days, even though it doesn't have all the functionality we wanted. We are just happy we got the basic functionality working.
What we learned
We learnt how to build a full stack ai web application, and how to integrate ai into a full stack project.
What's next for onTrack
Building out all the features that we wanted to build but couldn't due to time constraints. These include making the ai responses clearer, more actionable and providing greater detail. Additionally, we would like to make it produce a graph related to the users question that is related to their current prompt, helping users visualise their finances.
Built With
- basiq
- express.js
- groq
- javascript
- react
- supabase
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