Configuring Evidence, Confidence and Human Review in Quantin
A practical framework for evidence requirements, confidence signals, review thresholds, and escalation paths across Quantin intelligence workflows.
Confidence is useful only when it changes how a workflow behaves. In Quantin, evidence, uncertainty, and review rules should be configured together so that high-impact decisions receive stronger controls than routine summaries.
Define evidence requirements by claim type
Not every statement needs the same support. A summary may rely on one authoritative document, while a market or operational recommendation may require independent sources, freshness checks, and structured data validation. Define the minimum evidence class for each output field.
Interpret confidence as a workflow signal
A confidence value is not a guarantee of correctness. Treat it as one input to a policy decision. Combine it with source quality, disagreement, missing fields, novelty, and the cost of a wrong action.
Illustrative review policy
- Low impact: allow automatic completion when evidence is complete.
- Medium impact: require review when confidence or source quality falls below the accepted range.
- High impact: always require named human approval, regardless of confidence.
Make disagreement visible
When sources conflict, preserve both positions and identify which authority was preferred. A reviewer should see the disagreement, the selection rule, and the effect on the final recommendation.
Design an escalation path
- Pause the proposed action.
- State the missing evidence or violated policy.
- Route the case to the correct owner.
- Set an expiry time for the pending decision.
- Record the reviewer outcome for later evaluation.
Review the reviewers
Monitor approval rates, override reasons, response times, and outcomes. Frequent overrides may indicate weak instructions, poor source selection, or a policy threshold that does not match operational reality. Human review is part of the system and should be measured like any other component.
The goal is not to maximize automatic approvals. It is to make every decision proportionate to its evidence and potential consequence.