Improve Contract Intelligence with Optical Character Recognition (OCR) Accuracy

Optical character recognition (OCR) is the foundation of reliable contract intelligence and data extraction, writes Achint Agarwal of Pramata. While artificial intelligence (AI) often receives the most attention in contract analysis, OCR plays a critical role in determining whether contract data can be accurately searched, analyzed, and interpreted in the first place.

OCR is a technology that converts visual representations of text into digital content that computers can process. The technology transforms non-searchable PDFs into machine-readable text. It identifies characters from scanned images, reconstructs text, and outputs it in a format suitable for search and analysis. First, OCR systems enhance image quality, correct scanning issues, segment text into recognizable components, and apply pattern recognition to identify letters and numbers. This conversion creates the structured content necessary for downstream contract intelligence functions.

Nevertheless, the complexity of enterprise contract portfolios presents significant challenges. Many organizations maintain large collections of legacy agreements that include poor-quality scans, unusual formatting, handwritten notes, exhibits, schedules, signatures, stamps, and other elements that can interfere with text extraction. 

Agarwal emphasizes that successful contract intelligence begins with a reliable, OCR accurate, text foundation. AI systems can only analyze information they are able to read correctly, making OCR a critical prerequisite for extracting meaningful insights from contracts. Although OCR often operates behind the scenes, its performance ultimately influences the effectiveness of every layer built on top of it. For organizations seeking reliable contract intelligence, accurate OCR is not merely a supporting feature but a fundamental requirement.