Document Processing

What is Document Processing?

Document processing is the end-to-end workflow through which documents are received, interpreted, and acted upon. It spans every stage from initial intake through to integration with downstream business systems.

Key stages in the document processing workflow

• Intake: Receiving documents from any channel or format
• Data extraction: Identifying and pulling relevant fields and values
• Validation: Checking extracted data for accuracy and completeness
• Routing: Directing documents or data to the appropriate process or team
• Integration: Passing structured data into downstream business systems

How automated document processing works

Automated document processing applies a range of AI technologies to handle these steps without manual data entry for routine documents. These include:

• Optical character recognition (OCR): Converts document images into machine-readable text
• Machine learning (ML): Trains models to recognize document types, fields, and layouts
• Natural language processing (NLP): Interprets meaning and context within document content
• Generative AI: Enables zero-shot document handling, data augmentation, and content enrichment

Straight-through processing and human-in-the-loop handling

In practice, intelligent document processing (IDP) systems operate on a spectrum between fully automated and human-reviewed processing:

• Straight-through processing (STP): Straightforward documents with high extraction confidence are handled end-to-end automatically, with no manual intervention required.
• Human-in-the-loop (HITL) handling: Documents with low confidence scores, data anomalies, or exceptions are routed to human reviewers. Their corrections feed back into the system to improve model accuracy over time.

This combination of automation for routine cases and HITL handling for exceptions is what allows IDP to operate at enterprise scale without sacrificing accuracy.