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MoneyMind

We built MoneyMind to use AI for giving personalized financial advice, enhancing your portfolio’s strength and potential.

Inspiration

Fueled by our passion for finance and teaching, we aim to guide others towards long-term financial independence and success.

What it does

MoneyMind is a web app where users can log in (via Google) to get general stock portfolio advice or personalized insights based on their individual portfolios. Our application scrapes news websites to create a comprehensive analysis of market sentiment, helping users identify trending stocks and make informed investment decisions.

How we built it

We developed the product by leveraging unique APIs provided during the hackathon, harnessing the creative power of OpenAI's LLMs, and strengthening the front-end and back-end with Visual Studio.

Challenges we ran into

This hackathon presented greater challenges than anticipated. Our team was committed to creatively integrating numerous APIs. When integrating Hume's API, we were confronted with the complexity of interpreting over 50 emotions in its output. To quantify whether text conveyed positive or negative sentiment, we formulated a weighting system, assigning appropriate values to each emotion based on its intensity. Additionally, we encountered various issues with OpenAI's LLM models. Their output often didn't match our preferred format, necessitating quick thinking to convert disorganized text with scattered newlines into structured output suitable for our needs.

Accomplishments that we're proud of

We are proud to have quickly familiarized ourselves with multiple APIs during this challenging hackathon. Despite the hurdles, we are proud of our team's dedication to harnessing the potential of these APIs and creating an educational resource for the general public.

What we learned

We learned that the best way to start was to jump right in. At the beginning of the hackathon, our members were inexperienced with many of the sponsor's technologies. Now, we depart with invaluable lessons and enhanced skills. We loved the experimenting and innovating aspects of integrating various technologies across different aspects of our solution.

What's next for MoneyMind

We hope to add more API implementations that can better predict the direction that the stocks are trending towards and thereby increase the accuracy of the specific recommendations offered to the users with financial portfolios.