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Model governance vs agent governance
Model governance and agent governance are complementary. A safe model can still trigger unsafe actions if orchestration lacks runtime controls.
What teams need to get right
- Model governance covers evaluation, deployment, drift, and lifecycle controls.
- Agent governance covers tool permissions, approvals, and runtime enforcement.
- Enterprises need both to manage algorithmic and operational risk together.
How Stacksona helps
- Runtime guardrails focused on action-level risk, not just model metrics.
- Policy enforcement aligned with enterprise control objectives.
- Audit-ready evidence linking model outputs to governed downstream actions.
Why this matters now
As agent deployments move from prototypes to customer and operational workflows, governance needs to be embedded in execution paths. Teams that rely only on after-the-fact monitoring often discover risk too late.
