An automated document processing pipeline built for regulated environments where extraction accuracy and compliance validation are non-negotiable. The system ingests documents in bulk, extracts structured data via OCR and GPT-4, validates every field against configurable compliance rulesets, and routes approved documents downstream with a full audit trail.
Businesses operating under strict regulatory requirements were manually processing hundreds of documents per week. Each document required field-by-field extraction, validation against compliance rules (expiration dates, required signatures, format constraints, cross-field dependencies), and routing to the correct system. A single missed field or expired certificate could trigger fines or failed audits. The manual process was slow, inconsistent across reviewers, and left no reliable audit trail.
Built an automated pipeline using Tesseract OCR for text extraction, GPT-4 for intelligent field parsing and context-aware validation, and a configurable compliance rules engine stored in PostgreSQL. Each document passes through extraction, field-level validation, cross-field dependency checks, and a final compliance gate before being routed. Every step is logged with timestamps, confidence scores, and the specific rule that passed or failed. Documents that fail any rule are flagged for human review with the exact failure reason highlighted.
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