EquiFi

Inspiration

We were inspired by how difficult it is for many people to understand financial documents due to complex language, lack of trust, and limited financial literacy. We wanted to build a tool that makes financial information more accessible and empowering for everyone.

What it does

We were inspired by how difficult it is for many people to understand financial documents due to complex language, lack of trust, and limited financial literacy. We wanted to build a tool that makes financial information more accessible and empowering for everyone.

How we built it

We built EquiFi using Python and FastAPI for the backend, with an AI model to process and analyze uploaded documents. The frontend is a simple web interface that allows users to interact with the system easily, focusing on clarity and accessibility.

Challenges we ran into

We faced challenges setting up the development environment, managing dependencies, and ensuring files and static assets loaded correctly. Integrating AI outputs in a way that was both accurate and easy to understand also required careful iteration.

Accomplishments that we're proud of

We faced challenges setting up the development environment, managing dependencies, and ensuring files and static assets loaded correctly. Integrating AI outputs in a way that was both accurate and easy to understand also required careful iteration.

What we learned

We successfully built a working AI-powered web application within a short hackathon timeframe. We’re proud of creating a solution that directly addresses real-world financial accessibility issues while maintaining clean structure and functionality.

What's next for EquiFi

Next, we plan to expand language support, improve accessibility features, and add more detailed risk analysis. We also aim to partner with community organizations to better tailor EquiFi to the needs of underserved users.

Built With

• chat-gpt
• css
• html
• javascript
• openai
• python