The Challenge
FinDash is a financial intelligence platform for small and medium enterprises, providing automated financial reporting, cash flow forecasting, and AI-powered financial health insights. The platform integrates with business bank accounts, accounting software, and point-of-sale systems to aggregate a complete financial picture without requiring manual data entry. The target user is a business owner who understands their business but lacks formal financial training.
Our Approach
We began with a structured discovery phase to map existing workflows, identify technical constraints, and define the highest-value features for the initial release. Rather than trying to build everything at once, we established a phased delivery plan with working software at each milestone.
What We Built
Financial data ingestion runs through a Python/FastAPI ETL pipeline with source-specific connectors for each integrated data source. The normalized transaction model uses a double-entry bookkeeping structure internally, ensuring that the platform's financial calculations are reconcilable and auditable.
The AI insights engine uses OpenAI's API with a carefully engineered prompt structure that provides the model with structured financial data and specific analysis frameworks — the model generates natural language explanations, but all numerical analysis (trend calculation, cash flow projection, anomaly detection) is performed by deterministic Python code rather than the language model, preventing hallucinated financial figures.
"FinDash gives me the financial clarity I have always wanted for my business but never had the time or expertise to build myself. The AI explanations actually make sense to someone who is not an accountant."
The Results
FinDash completed its beta period with 800 SME businesses onboarded across 12 industry verticals and a 76% weekly active usage rate — a remarkably high engagement figure for a B2B financial tool. The NPS score of 67 places the product in the top quartile for B2B SaaS products globally.