AI Compliance Escalation Workflow
Teams looking for automated escalation mechanisms when AI encounters ambiguity or high-risk decisions.
Das Problem
Escalation is a first-class outcome in Corules alongside ALLOW and BLOCK. When a decision falls in a gray area — fraud score near the threshold, a decision that requires a higher authority level, an exception request — the system returns ESCALATE rather than making a probabilistic judgment. The escalation response carries full context: the specific condition that triggered escalation, the relevant policy rule, and all input data needed for the human reviewer to make an informed decision. Humans review what needs human review. Everything else flows automatically.
So löst Corules es
Corules's policy runtime evaluates structured context against compiled CEL expressions — returning ALLOW, BLOCK, or ESCALATE with a reason and audit ID.
Richtlinienbeispiel
// Escalation conditions are explicit in policy
fraud_score >= params.fraud_escalation_threshold
? "ESCALATE"
: fraud_score >= params.fraud_block_threshold
? "BLOCK"
: "ALLOW"
// Human reviewer receives: fraud_score, fraud signals, claim contextFrequently Asked Questions
Can escalation thresholds be tuned without code changes?
Yes. Thresholds are parameters, not hardcoded. Adjust fraud_escalation_threshold from 0.70 to 0.80 without touching policy logic.
What context does the human reviewer see?
The escalation response includes the specific condition that triggered it, all evaluated fields, the policy rule reference, and the full input payload. Reviewers have everything they need.