Our Position
Traditional governance models were built for static software and human-led workflows. Agentic systems introduce new risk vectors: emergent behavior, recursive task delegation, tool overreach, and opaque decision paths.
Governance, in this context, must be an architectural property—not a policy document applied after deployment.
What We Deliver
Agentic Governance Architecture
Includes: Autonomy zone definition, decision authority mapping, escalation thresholds, and kill-switch mechanisms.
Outputs: Autonomy zone map, Decision authority matrix, Escalation and override flows.
Agentic Risk Modeling
Includes: Cascading execution risk, tool misuse/privilege amplification, model drift, and coordination failures.
Outputs: Agentic risk register, Failure-mode analysis, Go/slow/stop deployment roadmap.
Control & Guardrail Design
Includes: Approval gates for high-impact actions, confidence thresholds, rate limits, and scope-bound tool access.
Outputs: Control layer architecture, Enforcement point definitions, Rollback logic.
Auditability & Explainability
Includes: Decision logging, trace capture, execution path reconstruction, and observability requirements.
Outputs: Decision logging specification, Traceability model, Explainability artifacts.
Governance Readiness Reviews
Includes: Maturity assessment, control gap identification, risk exposure analysis, and feasibility review.
Outputs: Readiness scorecard, Risk summary, Phased governance roadmap.
Who Delivers This Work
Engagements are led by senior agentic system architects with hands-on experience deploying autonomous workflows. This work is architectural, not theoretical.
When This Is a Fit
- Deploying or piloting agentic AI systems
- Require autonomy without loss of control
- Operate in regulated or high-risk environments
- Need governance that enables speed, not obstruction
Discuss Governance Architecture
Governed autonomy is not optional at scale. It is a design decision.