Intelligent Document Processing (IDP)
Organizations deal with large quantities of documents on a daily basis, which vary in terms of type, content or importance.
Ensuring the accurate classification of these files can become complex, especially if done manually.
Document classification is the process of assigning documents to relevant categories to facilitate their management and analysis.
What is intelligent document processing (IDP)?
Intelligent Document Processing (IDP) applies artificial intelligence (AI) and machine learning techniques to process both structured and unstructured documents, allowing the technology to read and process the content of documents like a human.
Through the use of OCR (a technology that helps extract text from images) and Deep Learning (a subset of machine learning), IDP is responsible for analyzing extracted data and automatically categorizing documents without human intervention.
IDP Advantages
- Operational efficiency: Manual data extraction and entry can be time-consuming and costly. IDP saves time and resources.
- Compliance: IDP reduces the risk of human error. Managing compliance tasks becomes easier, as there are logs that can be used in case of an audit.
- Customer experience: With IDP, employees are freed from the tasks of manually reading and processing documents, providing a better customer experience through greater efficiency in processes and decisions.
- Scalability: IDP is scalable and can be configured to process one type of document (e.g., invoices) and process only 100 documents per day, or it can be used to process dozens of different document types (invoices, complaints, bank statements, contracts, receipts, etc.) and process thousands of documents per minute.
Frequently Asked Questions about OCR, IDP and Document Intelligence
Answers to questions about OCR, intelligent document processing, data extraction and automatic classification.
OCR is used to transform text found in images, scanned PDFs, or photos of documents into searchable text. In document management, it makes it possible to find content that previously existed only as an image and can support data extraction. OCR is an important foundation, but on its own it does not replace classification, validation, or process automation. It is the basis for turning paper or images into searchable information.
OCR recognizes text in scanned documents or images; IDP interprets, classifies, and extracts information with more context. Intelligent document processing can use OCR, AI, machine learning, and validation rules to identify document types, populate fields, and trigger workflows. In short: OCR reads text; IDP turns documents into usable data. The choice depends on document complexity and the level of automation required.
IDP stands for Intelligent Document Processing. It is a technology that uses OCR, artificial intelligence, and business rules to classify documents, extract data, validate information, and route processes with less manual intervention. It is especially useful for invoices, contracts, forms, emails, and repetitive documents with relevant data. IDP is most useful when it feeds workflows, validations, and business integrations.
Artificial intelligence helps classify documents by analyzing content, patterns, fields, and context to suggest or automatically assign document types. This reduces manual work, speeds up registration, and improves information consistency, especially when the solution is trained with real organizational data and integrated with workflows. AI should work with rules, training, and validation to maintain trust in the results.