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OCR vs IDP

OCR converts document images into machine-readable text; IDP (Intelligent Document Processing) adds AI understanding on top to extract structured, contextual

technicalPublished 2026/06/05

FAQs

Is OCR obsolete?
No — OCR is a necessary component within IDP. IDP uses OCR to read characters, then adds AI to understand and structure them.
Which do I need for insurance documents?
Usually IDP, because the goal is to populate a system with structured data, not just convert an image to raw text.

Related Terms

  • Document Extraction (IDP)

    Intelligent Document Processing (IDP) is AI that reads unstructured insurance documents

  • Loss Run

    A loss run is a report from an insurer detailing a policyholder's claims history over a period

  • Intelligent Intake

    AI that automatically ingests, reads, and structures incoming submissions or documents at the point of entry — turning unstructured inputs into decision-read.

Related Items

  • Lido

    Template-free AI extraction of claims documents

  • Indico Data

    Intelligent intake for unstructured submissions

  • Heron Data

    Document automation for underwriting submissions

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OCR and IDP are often confused, but the distinction matters when evaluating insurance document tools. OCR (Optical Character Recognition) is the foundational technology that converts an image of text — a scanned form, a photographed document — into machine-readable characters. It answers 'what does this say?'

IDP (Intelligent Document Processing) builds on OCR to answer 'what does this mean?' It layers natural language processing, machine learning, and often document-layout understanding on top of OCR to extract structured, contextual data: this string is the named insured, this number is the deductible, this section is the loss history.

The practical difference: OCR alone gives you a wall of text that still needs human interpretation. IDP gives you structured fields ready to flow into your AMS, rating engine, or claims system. For insurance — where the goal is usually to populate a system from a document — IDP is what delivers value; OCR is just one ingredient.

When a vendor says 'we use AI to read documents,' the useful follow-up is whether they do true IDP (structured extraction with confidence scoring and review workflows) or essentially OCR with light parsing. The gap shows up on real-world messy documents.