SmartBalance

Inspiration

Our team was inspired by the Symplistic.ai challenge to build an Intelligent Banking Analyst. We wanted to address the problem of fragmented financial data by creating an AI-powered solution that turns complex financial information into clear, actionable insights. Beyond the competition aspect, including the opportunity to connect with company leadership, we were motivated to build something that could realistically help users better understand and manage their financial health.

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What it does

The Symplistic.ai Customer/Client-Facing Dashboard is an AI-driven tool that analyzes a user’s financial profile. It processes data such as income, expenses, savings, debt, transaction history, and spending patterns to identify risks and trends. The system outputs:

A financial risk level (Low, Medium, or High)
Three key risk signals
Three practical recommendations
A short, easy-to-understand summary Overall, it acts as a smart financial assistant that simplifies complex financial data into clear, useful guidance.

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How we built it

We developed the project using a full-stack architecture:

Frontend: TypeScript, React, Vite, Tailwind CSS Axios, React Dropzone for a responsive, user-friendly dashboard
Backend: Python, FastAPI, Uvicorn, Pydantic, Requests, Python-dotenv for handling data processing and logic
AI Integration: ContentIQ for generating financial insights through structured prompts
Additional Tools: Symplistic.ai ContentIQ for data ingestion and IBM watsonx Orchestrate for managing multi-step AI workflows

The system connects user inputs from the frontend to the backend, which structures the data and sends it through an AI prompt to generate consistent, professional financial analysis.

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Challenges we ran into

One of the main challenges was integrating multiple technologies into a seamless workflow, especially coordinating between Vite, Tailwind CSS, Python, and AI tools. We also had to carefully configure environments, including meeting strict Python version requirements (3.11–3.13) and ensuring compatibility with Vite and Node.js. Another key challenge was designing prompts and workflows that produced accurate, consistent, and evidence-based financial insights using AI tools like watsonx Orchestrate.

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Company Challenge

symplistic.ai

Build an AI agent that analyzes customer data to generate actionable financial insights, risk signals, and recommendations.

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Accomplishments that we're proud of

We successfully built a functional end-to-end system that processes both structured and unstructured financial data. We’re especially proud of our AI integration and prompt engineering, which enables the system to analyze important factors like credit utilization, savings adequacy, and debt burden to deliver meaningful insights. Most importantly, we created a tool that translates complex financial data into simple, understandable advice for users.

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What we learned

Through this project, we gained hands-on experience with full-stack development and AI integration in a real-world application. We learned how to structure and process diverse data sources, manage Python virtual environments, and build a modern Vite and CSS with Tailwind frontend. We also developed a strong understanding of prompt engineering and the importance of generating clear, reliable, and explainable AI outputs—especially in a financial context.

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What's next for SmartBalance

Moving forward, we plan to expand the system’s capabilities by incorporating more detailed financial data, such as transaction categories and advanced spending metrics. We also aim to improve automation in the backend and enhance the overall user experience with better visualization and personalization. Long term, we want to scale the platform to detect more subtle financial patterns and provide even deeper, more proactive financial insights.

** Completed Simplicity.ai company challenge!** First in person Hackathon!