FlowPilot

FlowPilot helps businesses prevent cash shortages by forecasting cash flow, identifying financial risks, and optimizing payment schedules with AI-powered insights—all in one platform.

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Inspiration

Businesses can generate revenue and still experience cash shortages because customer payments arrive late while supplier payments and other obligations continue to be due. We wanted to address this gap by building a platform that helps businesses anticipate financial risks rather than react to them after they occur.

This inspired us to build FlowPilot, a financial intelligence platform that brings cash-flow forecasting, risk analysis, and payment optimization together to support smarter financial decisions.

What it does

FlowPilot helps businesses understand their current financial position, anticipate future cash-flow problems, and evaluate payment decisions.

Its key features include:

Cash-Flow Forecasting: Projects future balances using expected inflows, outflows, receivables, and financial obligations.

Risk Analysis: Identifies potential cash shortages and reserve breaches before they become critical.

Payment Optimization: Evaluates payment schedules to help businesses manage liquidity and prioritize financial obligations.

Financial Dashboard: Provides a centralized view of company accounts and financial insights.

AI-Powered Assistance: Makes financial information easier to explore through a conversational interface.

Our objective is to transform financial data into actionable insights that help businesses make more informed decisions.

How we built it

We built FlowPilot as a full-stack application with a modular backend, an interactive frontend, financial analysis logic, and a relational database.

Frontend: A web-based dashboard for visualizing accounts, forecasts, risks, and financial information.

Backend: Python and FastAPI for API development and business logic.

Database: PostgreSQL for persistent data storage.

Financial Analysis: Forecasting and risk-analysis logic to project future balances and identify reserve shortfalls.

Optimization: A heuristic-based approach for evaluating payment schedules against liquidity constraints.

AI Integration: A conversational assistant layer for exploring financial information.

Deployment: Docker for containerization and Kubernetes with Minikube for deployment and service orchestration.

We also developed and tested API endpoints and automated tests to validate core application behavior and important edge cases.

Challenges we ran into

One of our main challenges was making financial calculations reliable across different scenarios. Forecasting requires careful handling of expected transactions, dates, and account balances, while risk analysis must distinguish between a negative balance and a balance that falls below a required reserve.

Handling multiple currencies was another challenge. Balances in different currencies cannot be combined meaningfully without a reliable conversion mechanism. Our current approach keeps currencies separate where conversion is unavailable, which remains an area for improvement.

Deployment also required significant debugging. We configured database connectivity, Kubernetes deployments and services, and communication between the frontend and backend. We encountered a frontend API configuration issue that caused the browser to send requests to an older local endpoint, teaching us the importance of validating the complete application path rather than testing individual services alone.

These challenges encouraged us to test systematically, investigate root causes, and preserve working components while improving the system.

Accomplishments that we're proud of

We are proud to have brought together several important financial capabilities in one working application instead of treating forecasting, risk analysis, and payment planning as isolated features.

Our accomplishments include:

Building a functional backend with APIs for financial data, forecasting, risk analysis, and optimization.

Connecting the backend to PostgreSQL for persistent data management.

Developing a dashboard that presents financial information in an accessible format.

Writing automated tests for important application behavior and edge cases.

Containerizing the application and deploying its frontend and backend through Kubernetes.

Establishing communication between the Kubernetes application and the existing database while preserving the working local demo environment.

Most importantly, we turned an idea about proactive financial management into a working application that we can test, demonstrate, and continue improving.

What we learned

Building FlowPilot strengthened our understanding of full-stack development, database integration, API design, financial calculations, and application deployment.

We learned that a useful forecast is only part of the solution: financial insights must also explain potential risks and support feasible actions. We also learned why multi-currency calculations require explicit assumptions, why automated tests matter for financial logic, and why reliable service configuration is essential when deploying distributed applications.

Working with Docker and Kubernetes gave us practical experience with container images, deployments, services, environment variables, networking, and debugging across application layers.

The project reinforced an important lesson: building a useful financial tool requires not only generating insights, but also making those insights understandable, testable, and actionable.

What's next for FlowPilot

We plan to make FlowPilot more accurate, explainable, secure, and production-ready.

Our next steps include:

Improving forecasting models and measuring their accuracy against historical data.

Enhancing payment optimization to account for due dates, payment priorities, penalties, and business constraints.

Adding reliable exchange-rate support for multi-currency cash-flow analysis.

Providing clearer explanations of detected risks and the impact of recommended actions.

Expanding scenario simulation so businesses can compare alternative financial decisions.

Strengthening authentication, authorization, and data security.

Improving monitoring and deploying the application to reliable cloud infrastructure.

Our long-term vision is to help businesses move from reactive cash management to proactive financial decision-making.

FlowPilot — Forecast. Optimize. Grow.

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