Human correction provenance
Teach keeps the source trace and authority link instead of turning the correction directly into production policy.
SOLUTION
Support AI teams
Turn recurring support corrections into reviewed behavior, then test escalation and policy changes before they reach customers.
THE PROBLEM
Support teams see the same corrections repeatedly: when to escalate, when not to issue another credit, which exception applies, and which facts matter. Those decisions are easy to lose in tickets and prompt edits.
WORKFLOW
From correction to governed runtime.
- 01
Start from the exact support trace that was wrong.
- 02
Capture what was wrong, what should have happened, relevant registered facts, scope, and a counterexample.
- 03
Review the correction as governed evidence.
- 04
Evaluate the candidate behavior on representative and high-risk cases.
- 05
Release the exact revision and observe online health before broader promotion.
WHAT IS GOVERNED
Keep authority separate from execution convenience.
Counterexample boundary
Reviewers can state where the correction should not apply so learning does not silently broaden scope.
Escalation visibility
Runtime explanation can show which authority layers applied or were skipped for the support decision.
FAILURE STATES
Important failures stay visible.
- Insufficient teaching authority blocks evidence creation.
- A broad correction still requires evaluation and release authority before production.
- Missing immutable trace provenance is shown as unavailable rather than reconstructed as fact.
INTEGRATION SURFACE