Super Simple Stocks

App Home Screen
App Portfolio Screen
App Notifications Screen
App Settings Screen
App Researching Screen
App Results Screen

Inspiration

Investing is an important step in growing long term wealth, however it is a complicated process that requires extensive research. Good investment tools are often locked behind paywalls and hard to understand data. We want to democratize smart investing for everyone by making it as accessible as possible, and free!

What it does

Uses a multi-agent architecture to perform extensive research about stocks, including current world news, prices, and history and present its findings in a human readable form. It also can analyze stocks already in a user's portfolio. It uses real time data from stock API's to ensure up to date information. It will periodically research about a user's chosen stocks even without their input and alert them if current news could have an effect on their investments.

How we built it

We initially prototyped it in Google AI Studio before moving to Visual Studio Code. We used a mixture of our knowledge combined with Google Gemini, OpenAI Codex, and GitHub. We built a multi agent architecture with multiple API’s to make sure it performed as well as possible.

Challenges we ran into

Making our idea come to life in the ways we had imagined it without making too many compromises for speed. Deciding which direction to go with the User Interface to maintain an easy to use beginner friendly theme. Finding out how to make it free for the user without adding any major inconveniences or annoyances.

Accomplishments that we're proud of

The clean minimalistic beginner friendly design that encourages new investors to think wisely about starting out in investing. The multi agent architecture that outperformed the S&P 500 by a large margin.

What we learned

How to collaborate using git, using a multi agent architecture for extended research, and prompt engineering. Tool calls with model context protocol.

What's next for Super Simple Stocks

Implementing the ads to make it free (cover the cost of API calls), and implement data parsing for real portfolios to improve user experience. Improve mobile compatibility and also improve the prediction models. Getting a custom domain to host the app and expanding knowledge about it.