Ragaroes

Inspiration:

Financial Analysts and Day Traders may need more specific information for how they may need to monitor their investments. With RAG, they are able to find high accuracy and precision for which investments are highly profitable.

What it does:

Ragoroes is a financial website where you can ask specific information about your financial trading decisions. Using RAG, Ragoroes finds the most accurate information based upon the newest stock data.

How we built it:

We had a front end, backend, and data pipeline. Next Js for the frontend Llamaindex, astra db, Langchain, Fast API, Python, pandas, and OpenAI for the backend. Yahoo Finance ( stock data) was found through the finance data.

Challenges we ran into

Connecting the front end and back end was a hassle when wiring.

Accomplishments that we're proud of

We are proud of the data we were able to find and learn about stock data

What we learned

We learned how using RAG can mitigate hallucinations, and chunk specific data for accurate derivatives of past stock data.

What's next for ragaroes

We look to implement and find more inspiration from day traders and investment bankers to help them by using AI.

Built With

• astradb
• datastax
• llamaindex