Intelligent Invoice & Document Processor

SMBs spend enormous time on manual data entry from invoices, purchase orders, and receipts. Finance teams key the same data into accounting systems by hand — introducing errors, delaying cash flow visibility, and burning hours that should go to higher-value work.

Designed and developed an Intelligent Invoice & Document Processor that automatically extracts, classifies, and validates data from invoices, purchase orders, and expense receipts using OCR and large language models — posting structured, validated results directly into the client's accounting system.

The solution handles the full document lifecycle: from ingestion of scanned PDFs, mobile photos, and email attachments through to confident, rule-validated posting — with a human-in-the-loop review queue catching anything the model flags as low-confidence.

Documents are ingested via email, upload, or automated inbox monitoring and processed through an OCR pipeline that normalises varying layouts, languages, and scan quality. Extracted fields are passed to an LLM layer that classifies document type, extracts structured data, and enriches records with context from the client's vendor and chart-of-accounts data.

A validation engine checks extracted data against configurable business rules — duplicate detection, amount thresholds, vendor whitelist checks — before posting to QuickBooks, Xero, or a custom ERP via REST API. Low-confidence extractions are routed to a human review queue, keeping humans in the loop without slowing down the majority of documents that clear automatically.