Finance OCR

Finance OCR turns uploaded finance documents into structured records through OCR, field parsing, validation, and a human review screen.

Raw OCR text is not enough for finance workflows. Teams need reliable fields, review history, and validation before data is exported.

Reduce manual entry while making extracted values reviewable, auditable, and easy to correct.

• Upload service for document intake and storage metadata.
• OCR worker for text and bounding-box extraction.
• Parsing layer for invoice number, date, vendor, amount, tax, and line-item candidates.
• Review dashboard for correction and export status.

• Document queue with processing states.
• Extracted field confidence and correction UI.
• Validation rules for totals, required fields, and date formats.
• CSV or accounting-system export placeholder.

• OCR using PaddleOCR.
• Layout-aware field extraction strategy.
• Post-processing rules for finance-specific formats.
• Optional LLM cleanup for ambiguous vendor names or descriptions.

1. 1User uploads invoice or receipt.
2. 2Backend stores file metadata and pushes processing job.
3. 3OCR worker extracts text, boxes, and candidate fields.
4. 4Validation layer marks missing or suspicious values.
5. 5Reviewer fixes fields and exports structured data.

• Different document layouts across vendors.
• Handling poor scan quality and rotated images.
• Avoiding silent mistakes in financial values.

• Use deterministic validation for totals before relying on LLM cleanup.
• Keep human review mandatory for MVP finance exports.
• Store original OCR text for audit and debugging.

Result metrics are pending. Add real extraction accuracy, review time, and manual-entry reduction after testing with sample documents.

• Add table extraction for line items.
• Add vendor-specific templates for high-volume vendors.
• Add confidence calibration with labeled documents.