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Optical Character Recognition (OCR) has long served as a foundational technology for digitising document content, converting scanned images into editable text through pattern recognition algorithms.

OCR (Optical Character Recognition) has been around for over a century and has evolved significantly since the early 2000s. Vendors began enhancing OCR with algorithms to correct basic recognition errors, improving extraction and accuracy to some extent. But OCR has a fundamental flaw: its performance is limited by the quality of the inbound document, which the receiver cannot control.

Many organisations struggle to automate 2- and 3-way matching when posting supplier invoices into their finance systems. Why? Because matching flawed data is a guaranteed path to failure.