Document AI, or Intelligent Document Processing (IDP), is an AI technology to automate the data extraction, interpretation, and processing of information from unstructured documents. Unstructured documents include various types of files, such as invoices, receipts, contracts, forms, and reports, which are typically stored in formats like PDF, Word, or scanned images.
Document AI uses a combination of techniques, including machine learning, natural language processing (NLP), OCR, and computer vision, to understand and extract relevant information from documents. These technologies enable the system to “read” and interpret documents much like a human would, extracting key data points, recognizing patterns, and understanding the context.
The main goal of Intelligent Document Processing is to automate manual and repetitive tasks involved in handling large volumes of documents. By automating the extraction and processing of information, IDP systems can significantly improve efficiency, accuracy, and speed in document-intensive processes. Some common applications of document AI include:
Data Extraction: Automatically extracting specific data points, such as customer names, addresses, dates, invoice numbers, or product descriptions, from documents and populating them into structured databases or systems.
Document Classification: Categorizing documents into different types or classes based on their content or purpose, such as distinguishing between invoices, purchase orders, or contracts.
Information Validation: Verifying the accuracy and consistency of information within documents or across multiple documents, identifying discrepancies or errors.
Workflow Automation: Streamlining document-driven processes by automating tasks such as document routing, approval workflows, or triggering actions based on specific conditions.
Compliance and Regulatory Requirements: Assisting in compliance with regulations by automatically analyzing and extracting required information from documents, ensuring adherence to specific standards or guidelines.
Intelligent Document Processing systems can be customized and trained to handle specific document types and domains, improving accuracy over time through machine learning techniques. These systems are increasingly being adopted by organizations across various industries to reduce manual effort, increase productivity, and improve data quality in document-centric workflows.
Regenerate response
