Real-Time DMAIC for AI Governance

From Periodic Review to Real-Time Control

In traditional quality management, DMAIC is a project methodology. A team defines a problem, measures the baseline, analyses root causes, implements improvements, and puts controls in place. The cycle might take weeks or months.

That cadence does not work for autonomous AI agents that make thousands of decisions per hour. By the time a periodic review identifies a quality problem, the agent has already compounded it across thousands of actions.

Corvair's patent-pending system hardcodes the DMAIC cycle into the governance engine's real-time control loop. Every agent action passes through all five phases in milliseconds.

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Define: The Registry Baseline as Commander's Intent

The Agent Registry provides the signed, authoritative baseline for each agent. This baseline constitutes what "correct" looks like:

• Identity bindings: Cryptographic proof of who this agent is
• Approved capabilities and tools: What the agent is allowed to do
• Data domains: What information the agent may access
• Delegation boundaries: Who can invoke this agent and what authority transfers
• Policy thresholds: Quantitative limits that trigger governance responses
• Mission and Intent (Layer 10): The Commander's Intent specifying purpose, scope, and outcomes

The Define phase is not static. The baseline is version-controlled and evolves as stewards refine the agent's profile based on operational experience. Every baseline change is signed and auditable.

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Measure: Dynamic Risk Scoring on Every Action

Upon a privilege request, the governance engine measures the live context:

• Identity validation: against the Registry record
• Dynamic Blast Radius: computation using the graph-based risk engine
• Multi-Dimensional Risk Vector: calculation spanning operational, data, and financial dimensions
• Operational Waste metrics: Permission Waste, Capability Waste, Exposure Waste, Transport Waste, Defect Waste
• Runtime telemetry: capture recording the observed operational reality

This is not sampling. Every action is measured, scored, and recorded. The measurement feeds both the immediate decision (Analyse) and the long-term improvement loop (Improve).

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Analyse: Policy Evaluation with Causal Explanation

The Policy Decision Point evaluates measured risk against version-controlled policy thresholds sourced from the Registry. It produces one of four outcomes:

1. Grant: Action is within policy. Proceed with minimal credentials.
2. Deny: Action violates policy. Block with explanation.
3. Downgrade: Action is in a grey band. Reduce scope and proceed with reduced authority.
4. Sandbox: Action requires observation. Execute in an isolated environment with enhanced monitoring.

Critically, every decision includes a causal explanation that records the policy rule version(s) applied and the reasoning path. This is not just a pass/fail flag; it is a complete audit trail of why the decision was made, traceable to specific policy versions and risk calculations.

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Improve: Feedback to Registry and Threat Catalogue

Runtime decisions and telemetry drive design-time improvement through a closed feedback loop:

• Stewards refine capabilities, scopes, delegations, and policies in the Registry based on runtime patterns
• Threat Landscape Catalogue is tuned with newly observed attack patterns and risk vectors
• Simulation Engine supports what-if analysis before committing changes
• CI/CD Governance Gate enforces improved configurations by blocking non-conformant builds

The Improve phase closes the loop between runtime observation and design-time governance. Problems identified in production automatically surface as improvement candidates, and improvements are validated through simulation before deployment.

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Control: Ephemeral Credentials with Deterministic Revocation

The Provisioning Orchestrator exercises inline control:

• Minimal, time-boxed credentials: consistent with the Registry baseline (no standing privilege)
• Deterministic revocation: on completion, timeout, risk escalation, or publication of new signed policy/catalogue versions
• Automatic containment: when conditions change: step-up authentication, privilege reduction, or quarantine
• Non-repudiable audit logging: of every credential lifecycle event

Control is not optional. It is architecturally enforced. Agents cannot bypass the credential system because the governance engine is the only path to the resources they need.