GoGetters

Model that shows both if you held money in the company or if you put money with our model
Dashboard of website, displays risk score, 30 day graph or YTD, and different companies

Inspiration

We were inspired by the fact that most retail investors struggle to understand complex financial statements and risk metrics.

What it does

Our project is a financial risk analysis and autotrading web app designed to democratize access to financial insights. By simplifying these signals into clear Low / Medium / High risk scores, we empower anyone to make more informed investment decisions.

How we built it

We built it by using React.js for Frontend, and we used Python scripts for parsing from yfinance, and stored it within an Aerospike database. Also used API pulls from Gemini for Investment Analysis Summary.

Challenges we ran into

Fine-tuning evolutionary AI models proved to be a major struggle for us, as it caused many problems and was hard to debug what was going wrong.

Accomplishments that we're proud of

At the end, actually getting a working AI model that works on 15 generations made us very pleased with what we did.

What we learned

We learned how to translate abstract financial theories (like Beta, Altman Z-Score, and Sharpe Ratio) into usable code and APIs

What's next for GoGetters

Autotrading Engine — extend the risk analysis system into an intelligent trading assistant that can automatically execute low-risk, high-reward trades on behalf of users. Expanded Coverage — integrate more asset classes beyond large-cap equities, including ETFs, small caps, and crypto, to give users broader visibility. Smarter Risk Models — incorporate machine learning and news sentiment NLP to refine risk scores dynamically and adapt to fast-changing market conditions. Personalization — allow users to set their own risk tolerance levels so the dashboard tailors insights to their individual investment style. Mobile App — launch a lightweight iOS/Android app for on-the-go access, making GoGetters a true pocket risk advisor. Community Features — add social and educational layers, where users can share insights, compare portfolios, and learn financial literacy together.