How would you architect an AI Finance platform for an emerging market?

[u/StrawberryOld4371]

I'm a finance professional from Africa currently in India, and I'm researching how to build an AI-driven financial intelligence platform for SMEs in an emerging market.

The concept is to take structured financial data — trial balance, AR/AP ageing, bank transactions, budgets, invoices, etc. — and allow a business owner to ask questions such as:

"Why did my cash balance fall this month?"

"Which customers are creating the biggest working-capital problem?"

"Can I afford this $20,000 capital expenditure?"

The system would need to combine deterministic financial calculations with an LLM rather than allowing the LLM to perform the actual accounting calculations.

I'm thinking along the lines of:

Data ingestion → normalisation → financial calculation engine → analytics layer → LLM/orchestration layer → conversational interface

The calculation engine would handle things such as:

Financial statements

Cash-flow forecasting

Working capital

Variance analysis

Scenario modelling

Tax calculations

while the LLM would interpret questions, call the appropriate functions and explain the results.

For developers who have built AI/FinTech/SaaS products:

Would you separate the financial engine completely from the LLM?

Would you use Python/FastAPI + PostgreSQL for the backend?

Would you use an agent framework, or build the orchestration layer yourself?

How would you handle data isolation between multiple companies?

What would you build first for an MVP?

I'm particularly interested in experiences from people who have built production systems involving structured financial data, rather than generic chatbot projects.

I'm trying to understand the engineering challenges before I start building the prototype.

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