Problem
Accountants serving small businesses receive documents in every format imaginable and spend hours on manual data entry and chasing missing details before they can even start the real work.
Solution
Clients forward documents to a dedicated inbox or WhatsApp number. The system extracts vendor, date, amounts, tax and line items, matches them to a chart of accounts, flags anomalies and presents a review queue the accountant approves in bulk.
Target customer
Independent accountants and small accounting firms handling 20–200 SME clients.
Role of technology / AI
Language models with structured outputs perform extraction and categorisation; rules validate totals and tax; a learning layer adapts categories per client from corrections.
Business model
Monthly subscription per firm with tiers based on document volume; optional per-client add-on pricing.
MVP scope
Email-forwarding inbox, extraction for invoices and receipts, a review UI, export to CSV or one popular accounting tool. Manual fallback for failures.
Technology stack
Next.js or similar web app, PostgreSQL, OCR service, foundation model API with JSON schema outputs, queue for async processing.
Opportunity
Document handling is a universal, measurable pain; accuracy and time saved are easy to demonstrate in a trial.
Risks and challenges
Accounting-software vendors adding native features; accuracy on poor-quality photos; regional tax rule variations.
This is a concept shared for discussion. It is not a validated business and no outcome is guaranteed. Last updated 11 September 2026.