Project Overview

Businesses receive thousands of documents—mostly invoices, POs, receipts—in inconsistent formats.

These documents often live in email attachments, shared drives, or vendor portals, and are manually processed for bookkeeping, reporting, or compliance.

We built an AI-powered pipeline to automatically:

• Extract structured data from messy PDFs
• Store it in a searchable database
• Allow validation and downstream usage (reporting, export, integration)

This system works across invoice formats and line-item structures, adapting to both clean digital PDFs and noisy scans.

2. Core Problem

Manual document entry is:

• Slow – takes several minutes per invoice
• Error-prone – misread amounts or tax values lead to financial discrepancies
• Unscalable – growth in volume = growth in headcount or backlog
• Opaque – documents are not searchable or reportable without transformation

Off-the-shelf OCR tools often extract raw text, but:

• Can’t distinguish between fields and tables
• Lose relationships between data points (e.g., line-item tax per SKU)
• Don’t validate if totals match line sums or detect missing data