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Frequently Asked Questions
Do you have Questions for OCR vs Intelligent Document Processing(IDP) ?
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OCR converts document images into machine-readable text but does not interpret or validate the content. Intelligent document processing (IDP) builds on OCR by adding classification, structured field extraction, validation rules, exception handling, and workflow integration.
Basic OCR is suitable when documents have consistent layouts, require extraction of only a few simple fields, and when manual review or downstream controls can handle remaining validations without significant risk or delays.
IDP provides document classification, extraction of complex fields and line items, validation against business rules, human-in-the-loop review workflows, exception handling queues, and integration with downstream systems like ERPs or AP automation.
High variability in document layouts, mixed document types, or frequent format changes typically justify using IDP because it can adapt with machine learning or rules without needing many templates. Stable, uniform formats are usually manageable with OCR alone.
In both OCR and IDP, human review is critical to handle exceptions and low-confidence extractions. IDP typically offers structured review stations with confidence-based workflows, while OCR often relies on ad-hoc manual validation.
Accuracy should be measured not just by character correctness but by correct extraction of critical fields, validation success, match rates, and straight-through processing rates. Confidence scores are signals used for routing work but do not guarantee correctness.
Indicators include high exception volume, need to extract line items or tables, multiple document types requiring classification, complex business rule validation, matching against POs or master data, and operational requirements for automated routing and auditing.
A phased approach allows starting with OCR to handle stable document sets and simple extraction, then expanding to IDP as volume, complexity, or risk increases. It helps create measurable improvements and controls before scaling automation.
Planning should include gathering representative samples, defining document classes and required fields, establishing exception ownership, designing test and annotation plans, mapping ingestion and integration points, and setting up security, compliance, and change management processes.
OCR generally exports recognized text or PDFs with little built-in routing, often requiring middleware or RPA. IDP platforms commonly provide APIs, automated routing to queues or ERPs, status tracking, retries, and audit logs integrated within the workflow.
Key considerations include data classification and tagging, role-based access controls, encryption in transit and at rest, retention and secure deletion policies, audit trails of ingestion and human actions, vendor and deployment reviews, and defined exception and approval ownership.
Moltech Solutions Inc. offers tailored document processing automation solutions that align with existing workflows, controls, and systems. They assist in readiness assessments, workflow mapping, exception ownership design, and phased automation planning.
