While OCR has been a reliable tool for digitising printed text, its capabilities are limited to basic extraction. It reads and converts text but lacks the intelligence to interpret meaning or act on data. This makes OCR suitable for structured, fixed-format documents — but modern businesses deal with semi-structured and unstructured content like invoices, contracts and emails, where OCR struggles.
IDP bridges this gap by combining OCR with AI, machine learning and natural language processing. It doesn’t just read—it understands context, classifies data and integrates directly into workflows. Unlike OCR, which requires manual validation and rigid templates, IDP adapts over time, improving accuracy and scalability. For enterprises handling high document volumes and complexity, IDP delivers true automation, enabling faster, smarter decisions without sacrificing compliance.
“OCR is great at recognising text, but that’s where it stops. IDP goes much further. It understands what it’s reading, applies context and logic and enables true automation. OCR is about recognition; IDP is about understanding and automation.”
Pol Brouckaert
Director EU, Netcall
Practical applications of OCR & IDP in business
Example of OCR in business
OCR is ideal for simple, text-based documents where layouts are fixed and no handwriting or complex structure is involved. Typical uses include:
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Digitisation projects: Converting old paper records into searchable archives
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Searchable databases: Scanning printed reports for keyword retrieval
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Standard internal forms: Capturing data from consistent HR or finance templates.
Example of IDP in business
When documents vary in format, contain images or handwriting or need validation and routing, IDP becomes essential. Common use cases include:
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Insurance claims: Classifying claim types and extracting policy data
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Supplier invoices: Reading totals, taxes and PO references from any layout
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Customer onboarding: Processing IDs, forms and signatures for compliance.
Input for you leverages advanced document intelligence to optimise inbound workflows for the insurance and health insurance sectors. This approach enables highly accurate data capture and rapid access to critical information.
Since adopting IDP, they’ve cut claim processing times by 80% and achieved straight-through processing rates of 70–80% for many documents, with some reaching an impressive 95%.
Why OCR isn’t enough anymore
Traditional OCR was designed to digitise text, but it falls short for modern enterprise needs. Its limitations—manual review, error correction and frequent rework—prevent true automation. OCR struggles with variable document types like invoices, contracts and emails, often producing raw text strings without context or classification.
Why IDP changes the game:
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Contextual Understanding: IDP uses AI-driven document intelligence and machine learning to interpret data, not just read it
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Scalability: Handles high-volume, multi-format documents with minimal human intervention
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Actionable Insights: In insurance claims, OCR outputs an unclassified text string, while IDP delivers an AI-classified claim type and extracts key data points for immediate processing.
Traditional OCR was designed to digitise text, but it falls short for modern enterprise needs. Its limitations — manual review, error correction and frequent rework — prevent true automation. OCR struggles with variable document types like invoices, contracts and emails, often producing raw text strings without context or classification.
By combining OCR with advanced technologies, IDP enables accuracy, compliance and end-to-end automation — critical for complex workflows.
IDP vs OCR: Which technology should you choose?
Both OCR and IDP have their place — but the tipping point toward IDP comes quickly as document complexity, variation or volume increases.
Choose OCR when:
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You only need to digitise and store documents for search or reference
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Data extraction rules rarely change
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Inputs are simple, structured and predictable.
Choose IDP when:
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You handle mixed document types and formats such as PDFs, images, scanned forms and emails with attachments
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You need better handwriting recognition and interpretation of unstructured data, including handwritten notes or mixed printed and cursive text
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You process multi-page or complex documents such as contracts, claim forms or onboarding packs that include both visual and textual information
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You want extracted data to flow automatically into your business systems with built-in validation and confidence scoring
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Human review should focus only on exceptions, while automation handles the rest
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You aim for straight-through processing (STP) and measurable accuracy gains.
As document complexity, variation or volume increases, the tipping point toward IDP arrives quickly.
Discover how Netcall’s IDP software delivers 99% accuracy, end-to-end automation and faster decision-making.
Automate the future with Liberty IDP
Ready to move beyond OCR? While standard OCR is limited to simple text extraction, IDP uses AI to understand and validate complex data, positioning it as the ultimate choice for maximising ROI and ensuring long-term scalability.
Explore Liberty IDP, our IDP solution today.
About the author
Pol Brouckaert
Director of Netcall EU
Pol leads the company’s expansion across continental Europe from the Brussels office. He joined Netcall through its 2024 acquisition of Parble, an intelligent document processing (IDP) company where he served as CEO. Pol has built a career at the intersection of strategy, technology and financial services. Earlier, he worked as a strategy consultant at BCG, advising leading banks and insurers on digital and business transformation initiatives internationally. His expertise spans strategy, AI and technological innovation. Together with his team, he has helped numerous companies harness the benefits of intelligent document processing, one of the most mature and pragmatic use cases of AI.