Intelligent Document Processing

Intelligent document processing (IDP) is an AI document processing technology that automates the analysis and extraction of useful data from unstructured documents, converting images and scanned text into machine-readable texts using optical character recognition (OCR).

By combining OCR, natural language processing (NLP), machine learning, and other AI techniques, an intelligent document processing platform achieves comprehensive document understanding. Compared to manual processes, IDP not only significantly reduces human errors but also efficiently handles large volumes of documents, thus enhancing productivity and data accuracy.

To illustrate how diverse automated document processing can be, consider the following real-world examples:

• Healthcare: Hospitals use intelligent document processing solutions to organize patient records by extracting key information from forms and notes.
• Human resources:  HR leverages IDP solutions to assist in recruitment by comprehending resumes and automating payroll by recognizing pay details on slips.
• Legal: IDP applications in the legal field include contract analysis using NLP to understand terms.
• Finance: Intelligent document processing streamlines invoice processing and expense management by understanding payment details on documents in the finance industry.
• Logistics: In logistics, document processing automation helps to extract shipment details from documents for operational efficiency.

Intelligent document processing employs a suite of advanced technologies, each serving a unique role in transforming unstructured documents into valuable data:

• Optical Character Recognition (OCR): Identifies and digitizes text from images, converting them into machine-readable formats, whether handwritten, printed, or typed. This initial step is crucial for enabling further analysis.
• Natural Language Processing (NLP): Allows computers to analyze, interpret, and understand human language, which is critical for extracting data and understanding document nuances such as sentiment and intent. This capability allows IDP systems to process complex documents like contracts, emails, and forms with a high degree of accuracy.
• Machine Learning (ML): Machine learning algorithms are pivotal in intelligent document automation. They enable IDP systems to improve their accuracy over time, learning from each document processed, much like human learning.

While both OCR and intelligent document processing extract data from documents, IDP automation provides far superior accuracy and capabilities. Unlike OCR, which primarily focuses on recognizing characters and words, IDP employs machine learning, NLP, and computer vision to not only recognize text but also understand and derive deep insights from documents. These systems can categorize relevant entities, figures, and facts, providing a level of analysis that goes well beyond OCR’s capabilities, especially in handling handwritten, poor-quality, or non-standard texts.