Key Differences Between OCR and IDP? - iCustoms
- Freya Jane
- Director of Customer's Success
Businesses rely on modern technology, such as intelligent document processing (IDP) and optical character recognition (OCR) for effective documentation. OCR and IDP play important roles in automated data extraction and document processing, although their capabilities and applications differ. Many studies show an increasing demand for IDP and OCR for extracting and classifying documents.
As per market research,
“The global IDP market size was worth 1.75 billion USD in 2023, which is increased to 2.30 billion USD in 2024 and is expected to reach 19.32 billion USD BY 2032, showing a CAGR of 30.5% during the period of 2024-2032.”
This staggering increase in the demand for IDP and OCR necessitates a thorough understanding of both and the differences between them.
This blog will walk you through the differences between OCR and IDP.
What is OCR?
Optical character recognition was used in the early stages of reading the documents into the computer. To read the text and convert the machine-readable document from scanned photos or handwritten text. It is defined as:
OCR converts handwritten or scanned text into machine-readable text. It recognises and converts letter shapes, patterns, and combinations into editable and searchable data using algorithms and pattern recognition.
Working of OCR
The optical character recognition process is straightforward and uses a simple framework. It includes the input, reading, and giving the output in the form of machine-readable language. Its workflow operates on the following steps:
- Preprocessing: OCR software preprocesses images for analysis. Image improvement, noise reduction, deskewing, and normalisation guarantee optimal character identification.
- Analysing Images: OCR detects text in images. It segmented lines, paragraphs, and characters from the background. This step uses pattern recognition and machine learning.
- Analysing Images: The OCR algorithm then recognises characters within text regions. Recognition methods include feature extraction, template matching, statistical modelling, and artificial neural networks.
- Post-processing: Post-processing by OCR software improves accuracy. Language modelling, context analysis, and error correction refine text recognition. This step fixes recognition issues and improves output.
- Generating Results: Post-processing by OCR software improves accuracy. Language modelling, context analysis, and error correction refine text recognition. This step fixes recognition issues and improves output.
What is IDP?
Intelligent Document Processing (IDP) is an advanced form of the OCR feature that uses artificial intelligence to read and extract data. Unlike OCR, which primarily focuses on converting text from images or scanned files into a machine-readable format, IDP can interpret complex documents, understand context, and handle unstructured data efficiently.
It is defined as:
“Intelligent Document Processing (IDP) is an AI-driven technology that automatically ingests, classifies, extracts, validates, and processes information from a wide range of documents, enabling organisations to automate document-centric workflows with higher accuracy and efficiency.”
Working of IDP:
- Document intake: IDP technology uses the document in the form of either a text file (PDF or Word) or images for formatting it. Email or document management platform connectors can upload these documents manually or automatically.
- Document class: IDP classifies incoming documents. This process classifies documents by content, layout, or other properties using machine learning algorithms or established criteria.
- Data extraction: Intelligent processing of documents provides better extraction according to one’s particular requirements. While developing the software, one can specify the documents and things that need to be extracted.
- Data validation: IDP systems evaluate extracted data against patterns, formats, and business rules using predefined rules, templates, or machine learning algorithms. This stage detects data errors.
- Integration and automation: Organisational systems and workflows use validated data. The IDP system automatically populates databases, ERP systems, and other applications with extracted data. Predefined rules or conditions can trigger processes, actions, or notifications.
- Exception handling: The IDP system flags and sends exceptions to humans. Poor quality documents, imprecise data fields, and unrecognised patterns are exceptions. To verify data, humans can evaluate and correct exceptions.
- Analytical insights: The IDP system may analyse extracted data for insights and decision-making. Reports, trends, and data-driven analysis can be done with extracted data.
- Enhancing learning: Using machine learning and AI, advanced IDP systems learn from user interactions, document feedback, and data validation. It improves accuracy, recognises new document types, and adapts to changing document structures.
What is the difference between OCR and IDP?
| OCR | IDP |
| Converts scanned or handwritten text into machine-readable text. | Extracts text, tables, forms, and unstructured data with full context. |
| Limited to simple text extraction; no workflow automation. | Automates end-to-end document workflows, from validation to integration. |
| Struggles with complex layouts, fonts, or unstructured content. | Effortlessly handles complex documents and adapts to new formats. |
| Provides searchable/editable text but no actionable insights. | Delivers actionable insights, analytics, and data-driven decisions. |
| Requires manual error correction and intervention. | Intelligent exception handling reduces human effort and boosts accuracy. |
What Makes iCustoms IDP Stand Out?
Customs paperwork can be time-consuming, repetitive, and prone to errors, but iCustoms IDP changes all that. Designed specifically for the customs industry, it turns a tedious manual process into a fast, automated, and highly accurate workflow. Here’s why it’s different:
1. AI that understands your documents
iCustoms IDP isn’t just about reading text; it understands context. Using NLP, machine learning, computer vision, and generative AI, it can distinguish product names, HS codes, quantities, dates, and more, even if the document is handwritten or low-quality.
2. Easy document upload
Bring in all your files, PDFs, Excel sheets, or scanned images. Whether you drag and drop, email, or integrate through an API, the system organises everything in one secure hub.
3. Smart classification
Documents are automatically sorted into the right categories: commercial invoices, packing lists, waybills, or export documents. iCustoms IDP uses layout patterns and context, not just keywords, to make accurate decisions.
4. Powerful data extraction
Critical information is pulled out automatically, including HS codes, weights, dimensions, and supplier details. Tools like iCombine, iTeach, and iMarker let you merge data, train the AI, and fine-tune extraction for unusual formats.
5. Validation and auto-correction
Every piece of extracted data is checked for accuracy, consistency, and completeness. Low-confidence fields are flagged, and the system even suggests corrections based on past shipments, reducing manual review.
6. Consolidation and reuse
For large or repeated shipments, iCustoms IDP consolidates data into clean entries and stores it in iList, so you can reuse validated information instantly; no retyping, no mistakes.
7. Seamless submission
Once validated, the system automatically fills customs declaration forms like CDS and ENS and submits them directly to authorities. This ensures compliance and speeds up border clearance.
8. Time-saving and peace of mind
With automation handling the heavy lifting, your team spends less time fixing paperwork and more time moving goods. Accuracy can reach up to 99%, making customs processing faster, smoother, and far less stressful.
Wrapping up
Unlike generic automation tools, the Intelligent Document Processing (IDP) solution is built to handle the complexities of customs paperwork. It doesn’t just scan documents—it understands them. Using AI technologies like NLP, computer vision, and machine learning, it captures, validates, and organises data with up to 99% accuracy. From messy PDFs to handwritten notes, it ensures clean, compliant outputs ready for customs submission.
The result? Faster clearances, fewer errors, and peace of mind.
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About iCustoms
iCustoms is an all-in-one solution helping businesses automate customs processes more efficiently. With AI-powered and machine-learning capabilities, iCustoms is designed to streamline your all customs procedures in a few minutes, cut additional costs and save time.
Struggling to Extract, Catagorise & Validate Your Documents?
Capture & Upload Data in Seconds with AI & Machine Learning