ads-decision-flow

An auditable automated decision system requires a dual-brain adaptive workflow that routes events through risk scoring, a policy firewall, and human-in-the-loop escalation. This ensures administrative actions are logged to decision-memory tables for pattern learning and full auditability.

A dual-brain decision routing flow orchestrates actions between Brain A and Brain B deployment boundaries, applying a policy firewall to enforce governance. You need it to prevent inconsistent or unsafe automated actions by ensuring correct precedence for blocking, human review, or automated execution.

To enforce human-in-the-loop escalation, route decisions through a PolicyEngine firewall that evaluates confidence scores and triggers REQUIRE_HUMAN_REVIEW when thresholds demand it, logging the outcome to decision memory for auditability.

Yes, the adaptive decision workflow supports confidence scoring storage and decision memory persistence. It records outcomes into append-only decision tables, enabling priors and pattern learning over time to improve future routing decisions.

The best way to apply policy firewalls is using a precedence engine that strictly orders rules: BLOCK_ALWAYS, REQUIRE_HUMAN_REVIEW, REQUIRE_BRAIN_B, and ALLOW_BRAIN_A. This guarantees automation never bypasses governance before routing through the FsmActionBridge.

You should avoid dual-brain routing if your administrative actions lack defined policy rules or do not require auditability. Without a policy firewall to enforce precedence and decision memory for logging, the dual-brain overhead provides no governance value.