The Challenge : A major financial institution processes 20 million mortgage pages monthly across 1,400+ document types with 2,000+ data extraction fields. Documents arrive in varying quality (machine-readable text to scanned images), inconsistent formats and orientations, and unpredictable order. The "long tail" of infrequent document types and significant variation within categories (40+ bank statement formats) made traditional OCR approaches inadequate. Manual processing created delays, errors, and compliance risks.

The Pienomial Solution : Our three-stage autonomous pipeline handles the complete mortgage processing lifecycle

1. Pre-processing: Automated detection of document generation quality, automated preparation (page orientation correction, image enhancement), and "no assumptions" processing that handles any format
2. Classification: Pattern recognition-based classification into precise sub-types, continuous learning and reinforcement for improved accuracy, and lean models optimized for high-throughput processing
3. Analysis: Automated data extraction through triangulation with multiple algorithms, data format validation, signature relevance assessment through context and position analysis, and comprehensive field extraction across 2,000+ data elements