MoneyMentorAI

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  Logo

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  Banking page

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Inspiration

MoneyMentorAI was inspired by the need for an accessible, AI-powered assistant to guide individuals through complex financial decisions, including banking, investing, cryptocurrencies, and stocks.

What it does

MoneyMentorAI helps users make smarter financial decisions by providing personalized advice with data from reputable datasets and sources for banking, investments, crypto, and fraud detection.

How we built it

We used a React-based front-end and used Django for the backend. We used PostgreSQL with the pgvector extension to allow us to use a vector database to store all of our financial data from different sources. We then use an agentic RAG that does a similarity search between the query and the vector DB to retrieve the necessary data and display it.

Challenges we ran into

We actually ran into a massive problem this hackathon. Our original idea was to build an AI driving assistant using metrics from a camera and an accelerometer and have that data sent to insurance companies to show good driving. We had to pivot away from that entirely since none of the hardware we had worked as intended and we could not do any of the project anymore. So we only had 11 hours to build the current project we have now

Accomplishments that we're proud of

Building an application we are relatively proud of even after pivoting 12 hours into the hackathon, and we learned a lot about hardware, AI, software and much more.

What we learned

We learned a lot about using hardware with AI, learned about Arduinos and accelerometers, and using a camera as well. And we also learned more about vector databases and RAG agents.

What's next for MoneyMentorAI

We would love to expand the idea with more financial services, way more data, so we can have more accessible information than we do now.

Built With

• django
• openai
• postgresql
• python
• react
• terraform
• vector-database