Inspiration

What it does

SME Cashflow Predictor

Inspiration

We noticed that many small business owners work hard every day but still face cash flow problems. Most accounting tools show what has already happened, but they don't clearly tell owners what might happen next. Many businesses struggle because they find out about a cash shortage only when it's too late to pay employees, suppliers, or bills.

We wanted to build a simple tool that gives business owners an early warning and helps them make better financial decisions before problems happen.

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What it does

SME Cashflow Predictor is an AI-powered assistant that predicts future cash flow using business data from accounting and payment platforms like QuickBooks and Stripe.

Instead of showing complicated financial reports, it explains everything in simple language. For example, it can tell a business owner:

"Based on your recent sales and upcoming payroll, you may not have enough cash next Friday."

The platform also allows users to ask questions such as:

• Will I have enough money for payroll next week?
• What happens if sales drop by 15%?
• Can I afford to hire another employee?
• How much cash will I have next month?

The goal is to make financial planning easier, even for people without an accounting background.

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How we built it

The project is designed with a modern AI architecture.

• Frontend: Next.js and React
• Backend: FastAPI (Python)
• Database: PostgreSQL
• AI Model: Llama 3 for natural language explanations
• Forecasting: Time-series forecasting using historical income and expense data
• Data Sources: QuickBooks and Stripe APIs

The system collects transaction data, organizes it, predicts future cash flow, identifies possible risks, and then explains the results in simple, easy-to-understand language.

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Challenges we faced

One of the biggest challenges was working with financial data from different sources. Every platform stores information in a slightly different way, so combining everything into one clean format required careful planning.

Another challenge was creating predictions that are useful and easy to understand. A forecast alone is not enough—business owners also need to know why the prediction was made and what they can do about it.

Balancing technical accuracy with clear communication was an important part of the project.

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What we learned

Building this project helped us understand how AI can be used for real business problems instead of just generating text.

We learned about:

• Time-series forecasting
• Financial data processing
• API integration
• AI-powered explanations
• Building user-friendly dashboards
• Designing products that solve real-world problems

Most importantly, we learned that good AI should not only provide predictions but also explain them in a way that anyone can understand.

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Future plans

We plan to add more features, including:

• Bank account integration
• Mobile application
• Multi-currency support
• GST and tax reminders
• Invoice payment tracking
• Smarter forecasting models
• Personalized business recommendations
• Support for more accounting software

Our long-term goal is to build an AI financial assistant that helps small businesses stay financially healthy and make better decisions every day.

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for SME Cashflow Predictor

Built With

• ai
• ppt