Document classification that reduced manual sorting and errors
Manual document sorting looked simple until volume increased. A few invoices, a handful of contracts, some claims forms. Then it scaled. Hundreds of documents arrived daily through email, scans, and uploads. Staff spent hours reading, labeling, forwarding, and correcting mistakes. That was exactly where Intelligent Document Processing changed the equation. By using AI driven classification and data extraction, organizations reduced manual handling, improved accuracy, and created structured workflows from unstructured inputs. The shift mattered because document heavy operations were expensive. Research from McKinsey highlighted that knowledge workers spent a significant portion of their time gathering and processing information rather than analyzing it. When classification was automated, that time shifted toward higher value work. Why manual sorting broke at scale Manual sorting relied on human interpretation. A team member opened a document, decided what it was, renamed it, save...