Glossary

Optical Character Recognition (OCR) is a technology that converts the text contained in images, PDFs, and scanned documents into machine-readable data. In finance, OCR is the foundation that enables automation tools to extract key information, such as invoice numbers, amounts, supplier names, IBANs, or contract terms, from documents that were never designed to be processed digitally.

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Traditional OCR focuses on character-level detection: it “reads” pixels and turns them into text. But in modern financial operations, this alone is not enough. Documents vary in structure, quality, language, and formatting, and teams need more than raw text, they need reliable, structured data that can be reconciled, validated, and pushed into accounting or ERP systems.

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This is where AI-enhanced OCR changes the equation. Combined with NLP and machine learning, OCR becomes capable of understanding document layouts, identifying fields in context, and extracting line-level information with far higher accuracy. It supports messy PDFs, low-resolution scans, tables, handwritten notes, and multi-page contracts, while learning from corrections over time.

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Phacet integrates advanced OCR directly into its AI agents, allowing finance teams to process supplier invoices, payment documents, delivery notes, contracts, and bank statements with high precision. Extracted data is not only cleaned and structured but also traceable back to the exact source element inside the document, ensuring full auditability and compliance.

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To see OCR in action within Phacet, explore the Extract Payments from PDFs use case, which illustrates how accurate extraction underpins automated reconciliation and end-to-end financial workflow reliability.