Human-in-the-Loop Overview

Human-in-the-Loop (HITL) enables human verification and corrections to ensure accuracy of data extracted by Document AI processors before it is used in critical business applications.

It provides a workflow and a platform for your own or a partner workforce (humans referred to as labelers in HITL) to review, validate, and correct the data extracted from documents by Document AI processors.

Features

  • Confidence threshold filters to limit the number of documents going through HITL.
  • Labeler pool management, including task assignments and efficiency analytics by task and by labeler.
  • UI cues and features that reduce labeler handling time per document.
  • Analytics and metrics by task and by labeler, so you can streamline HITL operations.

Benefits

  • Risk mitigation - mitigate financial risks of critical data being incorrect - for example, invoice amounts, billing addresses, loan amounts, etc.
  • Simplify Exception Handling - Easily roll out a human review and exception handling workflow.
  • Workforce Efficiencies - manage, monitor and improve productivity of workforce managing human review.
  • Cost control - control costs of human review with configurable filters.
  • Data completeness - ensure extracted data is complete for downstream business applications.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025年11月05日 UTC.