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What are OCR and IDP?
OCR (Optical Character Recognition) is the technical foundation for converting text from images or scanned documents into machine-readable text. Traditional OCR recognizes characters—but does not understand context.
IDP (Intelligent Document Processing) goes much further: It combines OCR with AI to understand the content of documents. IDP identifies document types, extracts structured data (amounts, dates, line items), and integrates it into business systems—even without fixed templates.
Maturity Levels: Traditional OCR (text conversion only), template-based (fixed fields per document layout), IDP with ML (models learn from examples), multimodal LLMs (modern foundation models like Claude and GPT-4o understand documents holistically).
IDP is now within reach for small and medium-sized businesses—with off-the-shelf cloud services (Azure Document Intelligence, Google Document AI, AWS Textract) or LLM-based approaches. Instead of taking years, invoice processing, contract analysis, and form processing can become operational in a matter of weeks.
Best Practices for Document Automation
These six principles have proven effective:
- Start with one document type: Invoices are the classic choice—they provide a quickly measurable business case.
- Use confidence scores: Don’t accept everything blindly—require human approval for uncertain fields.
- Build in a feedback loop: Corrections made by staff members become training data.
- Ensure scan quality: Poor-quality scans render even the best AI helpless.
- Keep data protection in mind: Sensitive documents require European or on-premises solutions.
- Evaluate the LLM approach: For many document types, this will be the fastest route by 2026—without model training.
Common Mistakes in OCR/IDP Projects
We often see these pitfalls:
- Overly Ambitious Goals: Trying to handle all document types at once—the project becomes complex and expensive.
- Accepting poor-quality scans: Scans that are practically garbage—even the best AI delivers poor results.
- No human-in-the-loop: 95 percent accuracy means 5 percent errors—which require human correction.
- Template-based only: New document layouts immediately require a new template—not scalable.
- Data protection overlooked: Invoices stored in a U.S. cloud — a GDPR violation.
OCR vs. IDP vs. RPA
Three approaches to document processing:
- OCR: Converts images to text. Basic functionality—but doesn’t understand the content.
- IDP: Understands documents, extracts data. Uses OCR plus AI.
- RPA: Automates click-based processes — can enter IDP results into systems.
Document Automation with prodot
In a free initial consultation, we identify the most promising document type for automation and outline a practical pilot project.
As an AI partner for small and medium-sized businesses, we build IDP solutions in a pragmatic way—using cloud services, LLMs, or our own models. Always GDPR-compliant.
What We Offer
- AI Consulting — Use Case Selection and Implementation.
- Computer Vision — the visual foundation.
- NLP in the glossary — for text processing after OCR.
- Multimodal AI — a modern IDP approach.
