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Glossary

What is human-in-the-loopdocument review?

Human-in-the-loop means automation processes the confident cases end to end while humans decide the exceptions, inside the same workflow with full context.

Definition

Automation with an escalation path.

Human-in-the-loop (HITL) is the design pattern where software does the repetitive work and structurally involves people where judgment is needed. In document processing: extraction and validation run automatically, and documents that fail a check or fall below a confidence threshold park for a person to decide.

The point is not distrust of automation but honesty about its edges. A system that routes its uncertain 5% to a reviewer beats both the fully manual process and the fully automatic one that silently gets that 5% wrong. Reviewer decisions also become feedback that tightens the automated share over time.

Exceptions only

Humans see the documents that need them: failed checks, low confidence, unusual cases.

Full context

Reviewers see the document, the extracted fields and the failing check side by side, not a bare task.

Auditable decisions

Every accept, correction and rejection is recorded: who decided what, when, and why.

In practice

Review in MiruIQ.

MiruIQ ships a three-pane verify workspace (queue, record editor, page viewer with highlighted source regions); documents park at verify nodes in the pipeline and resume automatically once a reviewer decides, with edits preserved across runs.

FAQ

Human-in-the-loop (HITL) questions

What operations teams ask about HITL.

When does a document go to human review?

When you decide it should: verify nodes park documents on failed validation, low extraction confidence, missing cross-document consistency or rules you define (amounts above a threshold, specific document types, random samples for quality control). Everything else passes through untouched.

Does human review not defeat the point of automation?

No, because review is proportional to uncertainty, not to volume. At a 95% straight-through rate, ten thousand documents mean five hundred reviews instead of ten thousand manual entries, and each review is faster than manual processing because the data is pre-filled and the problem is highlighted.

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