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Automated Scanning, Segregation, Classification & OCR Extraction at Scale
The Retail Client processes over 2 million journal vouchers, each supported by one or more invoices submitted in both digital and original (physical/scanned) form. For audit, reconciliation, and regulatory compliance, every invoice linked to a general voucher must be retrieved, verified, and have 11 key data fields extracted and matched back to its originating voucher.
Handling this volume manually across an estimated 500,000 invoice pages presented three core problems:
TwigSystem designed and deployed an AI-driven Intelligent Document Processing (IDP) system to automate the full pipeline — from raw scanned pages to structured, voucher-matched data. The system performs three core functions:
Automatically detects invoice boundaries within bulk-scanned, multi-page batches — splitting continuous scans into individual invoice documents without manual sorting.
Each segregated invoice is automatically classified (e.g., by vendor, invoice type, or associated voucher category), enabling structured routing, storage, and retrieval.
Using OCR combined with ML-based data extraction, the system captures 11 predefined fields from every invoice.
Extracted data is automatically linked back to the corresponding general journal voucher, closing the loop between the financial record and its supporting invoice evidence — across both the digital and original copies submitted.
Note: field list to be confirmed against the client's actual 11-field specification.
Note: throughput, accuracy, and time/cost-saving metrics to be added once finalized for publication.
For a retail organization managing millions of financial transactions, invoice-to-voucher traceability is not optional — it is an audit and compliance requirement. This solution converts a manual, page-hunting exercise into an automated, accurate, and auditable pipeline, at a scale no manual team could sustain.