What is OCR and intelligent document processing?

OCR and intelligent document processing: definition

A scanned document is, to a computer, initially just an image. OCR recognizes characters in it and delivers text that can be searched or processed further. Open-source tools such as Tesseract are widespread, as are services from the major cloud providers. This step is the prerequisite for paper documents to be processed digitally at all.

Intelligent document processing (IDP) combines OCR with layout analysis, machine learning and, increasingly, language and vision models. It understands which entry is an invoice number, where the total amount is and which line items belong together, even if each supplier uses its own layout.

How automatic processing works

The typical flow: documents arrive by email, scan or upload, are classified, converted to text and broken down into fields. The software then checks whether the values are plausible, for example whether net, tax and gross add up or whether the order number exists in the ERP.

Each extracted field gets a confidence score. Reliable cases pass straight through; uncertain ones are presented to an employee for review with the relevant spots marked. The verified data goes through interfaces into ERP, accounting or DMS and is stored in an audit-proof way. This reduces manual work to the cases where a person is actually needed.

Real-world example: incoming invoices at a trades business

An electrical contractor receives invoices from wholesalers as PDFs, phone photos or paper. Until now, accounting typed in supplier, date, amounts and line items by hand. With IDP, the fields are recognized automatically, matched to the supplier and reconciled with the order. Accounting only checks flagged deviations.

Invoices in the structured e-invoice format need no text recognition, because they already contain the data in machine-readable form; since January 1, 2025, businesses in Germany have had to be able to receive e-invoices. For all other documents, IDP remains a major relief. What matters is that the business knows both paths and that storage stays uniform for all document types.

Limits, typical mistakes and imple­menta­tion

Poor scans, handwriting, stamps or unusual layouts lower the hit rate. You should therefore not promise full automation but plan for reviewing uncertain cases. For documents, the retention and traceability rules of the GoBD (German principles for proper bookkeeping) also apply; data protection must be considered too. The cost per document and training for employees also belong in the business case.

Nano Concepts develops document processing connected to ERP, DATEV and DMS so that documents arrive where they are needed without a media break. First we evaluate a sample of your real documents together and show which hit rate is realistic, before the solution is built.

• Start with one document type and a clear benefit, such as incoming invoices
• Plan plausibility checks and review of uncertain fields
• Standardize scan quality and intake channels
• Plan the connection to ERP, accounting or DMS from the start
• Clarify retention, GoBD and data protection