What Is Intelligent Document Processing?
Defining Intelligent Document Processing
Intelligent Document Processing (IDP) refers to a set of AI-assisted techniques used to extract, classify, and validate information from business documents. It builds on optical character recognition (OCR) by adding classification, field-level understanding, and validation logic, so that unstructured documents can be converted into structured, usable data.
Why Businesses Use IDP
Many organisations still rely on manual data entry to move information from documents such as invoices, forms, and identity records into business systems. This is slow, inconsistent, and difficult to scale. IDP automates the extraction step while including validation and exception handling, so teams can focus on reviewing exceptions rather than processing every document manually.
Core Components of an IDP Pipeline
A typical IDP pipeline includes document intake, document type classification, OCR-based text extraction, field and table extraction, validation against business rules, and export of structured data to downstream systems. Confidence scoring is often used to flag fields that require human review before the data is used.
Human Review Remains Important
IDP systems are designed to support, not replace, human oversight. Extraction accuracy depends on document quality, layout consistency, and configuration. A review workflow for low-confidence fields helps maintain data accuracy before it flows into critical business processes.
Related Product
A multi-document OCR and Intelligent Document Processing system that extracts, classifies, validates, and structures information from business documents.
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