"Invoice and Contract OCR: Document Automation with AI"

Entering invoices, contracts and forms into the system by hand is both slow and error-prone. Classic OCR has existed for a long time but was limited; it only worked with specific formats. Modern LLM-based OCR solves even a format it hasn't seen.

01. The Limits of Classic OCR

Classic OCR (Tesseract, ABBYY, etc.) reads line by line and says "this is what's written at that coordinate." To find fields correctly, a template definition is usually required. When the invoice's supplier changes, the template breaks.

02. LLM-Based OCR: The New Generation

Models like GPT-4V, Claude and Gemini read and understand the image directly. They answer the question "what's the total of this invoice?" without any template. This is an increase in both speed and flexibility.

03. Concrete Application Areas

Areas where LLM OCR is useful:

• Supplier invoices (200 different formats, one flow)
• Contract summary extraction
• Form and application reading
• ID and passport verification
• Shipping labels and dispatch notes

In each scenario, 90%+ accuracy is possible, with human verification added for critical fields.

04. The Process of Writing to the ERP

OCR doesn't end with reading; the read data must be written to the right field in the ERP. For this:

• Field mapping (the "Total" on the invoice → the "Grand Total" in the ERP)
• An approval flow (especially for high-value invoices)
• Exception handling (a human steps in when OCR isn't sure)

Without designing these, OCR is a half-solution.