Inspiration

We were inspired by the complexity of personal finance and the lack of accessible, intelligent guidance. Our app leverages AI and transaction analysis to empower people with smarter budgeting, effortless saving, and financial clarity.

What it does

The team’s project is an AI-powered financial assistant that helps investors budget, save money, and analyze transactions by integrating with their banking data.

How we built it

We brainstormed ideas related to business/finance and decided to focus on budgeting and a financial assistant that guides users toward better saving. We chose to use a modern web stack, focusing on performance, security, and user experience. The frontend was designed with an intuitive interface, while the backend efficiently handles data processing, authentication, and AI tuning. We integrated secure banking APIs to analyze hypothetical transactions and provide personalized budgeting advice, ensuring users receive accurate and actionable recommendations. The AI chatbot plays a central role, offering real-time financial guidance based on user data.

Challenges we ran into

One of the biggest challenges we faced was ensuring compatibility between frameworks, especially when deciding between TypeScript or JavaScript while transitioning our project. Authentication posed another challenge as we evaluated and worked with Auth0 and Clerk, each with its own setup complexities. Integrating the Plaid API for transaction access required navigating its authentication flow and data handling to ensure a seamless user experience. Lastly, fine-tuning our AI and machine learning models presented challenges when choosing the right model and optimizing it for performance.

Accomplishments that we're proud of

We’re proud of successfully connecting transaction information via the Plaid API, which is then sent to the AI chatbot to train and use the data as a reference in order to produce personalized financial advice. Another accomplishment we’re proud of is the interactive AI chatbot and transaction display, which effectively covers the core concept of the project.

What we learned

Throughout the development of this app, our team learned the importance of collaboration, adaptability, and perseverance. We gained valuable experience in integrating complex APIs, refining AI models, and troubleshooting compatibility issues, which ultimately strengthened both our technical and problem-solving skills.

What's next for Profit Prophet

Our plans for this app include enhancing the AI’s capabilities to provide even more personalized financial insights, such as predictive budgeting and investment recommendations.

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