Inspiration
Small businesses generate large amounts of financial data, but many owners still struggle to answer simple, important questions:
- How much cash will we have in the next few months?
- Can we afford to hire or invest?
- What happens if customers pay late?
- Which financial risks need attention now?
Accountants and financial advisers face a similar challenge when supporting multiple clients. Important insights are often spread across accounting systems, reports, and spreadsheets.
We built Finoya to turn complex financial data into clear forecasts, practical insights, and actionable next steps.
What it does
Finoya is an AI-powered cash flow management platform for small businesses, accountants, and financial advisers.
It helps users:
- Understand their current cash position
- Forecast future cash flow
- Identify financial risks earlier
- Test decisions through scenario planning
- Explore financial questions with an AI assistant
- Receive clear recommendations based on financial data
- Monitor multiple businesses from one dashboard
Finoya goes beyond showing what happened in the past. It helps users understand what may happen next and what they can do about it.
How I built it
Finoya was built as a cloud-based web application with a modern frontend and an API-driven backend.
The frontend uses React, JavaScript, Vite, Tailwind CSS, and React Router to create a responsive and accessible user experience.
The backend is built with Python and FastAPI. Azure OpenAI supports Finoya’s AI features, while Azure Cosmos DB and Azure Blob Storage are used for data storage and processing.
Finoya also integrates with services such as Xero for accounting data, Stripe for payments, and PostHog for product analytics.
Financial data is processed and presented through dashboards, forecasts, reports, scenario-planning tools, and AI-generated guidance.
Challenges I ran into
One of the biggest challenges was translating complex financial data into information that is accurate, useful, and easy to understand.
Financial data varies across businesses, industries, and accounting systems. Useful recommendations need to reflect the context of each business rather than provide generic advice.
Another challenge was balancing advanced financial analysis with a simple user experience. Many small business owners are not finance experts, so forecasts and recommendations must be clear without oversimplifying the underlying data.
We also needed to design AI responses that remain relevant to the user’s financial information and business question.
Accomplishments that I'm proud of
We are proud to have built a platform that makes financial forecasting and scenario planning more accessible to small businesses.
Finoya brings together accounting data, cash flow forecasting, AI-powered guidance, and multi-client monitoring in one platform.
We are also proud that the product supports both business owners and professional advisers while keeping the experience clear, practical, and action-focused.
What I learned
We learned that small businesses do not necessarily need more reports or dashboards. They need clearer answers to three questions:
- What is happening now?
- What is likely to happen next?
- What should we do about it?
We also learned that financial AI works best when it supports human decision-making rather than replacing professional expertise.
For accountants and advisers, the greatest value comes from identifying issues earlier, reducing manual analysis, and making proactive client conversations easier.
What's next for Finoya
Next, we plan to continue improving Finoya’s forecasting, scenario planning, AI guidance, and multi-client experience.
We also want to provide more tailored insights for different industries and business situations, so users receive recommendations that are more relevant to their specific cash flow challenges.
Our long-term goal is to make proactive financial management available to every small business, not only companies with access to a full-time CFO.
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