Event
Professional services · 18
AI Agent Governance
Controls what every agent may see, decide and do — with validation, traceability and human gates.
Business problem
AI Agent Governance · Not another CRM. Not an AI chat.
In the AI Agent Governance domain, critical signals are scattered across systems and teams. Decisions arrive late, ownership becomes unclear and the business sees the issue only after money, time or customer trust has already been lost.
How this domain operates
Example operating scenario
Decision
It combines business context, policy, priority and risk before choosing the next step.
Action
It initiates the controlled response: Agent registry and permissions.
Result
COS verifies completion, measures the effect and escalates when the expected result is missing.
Operational outcomes
From visibility to controlled execution.
01
Agent registry and permissions
02
Autonomy levels and approvals
03
Quality and cost control
04
Rollback and human hand-off
Signals COS acts on
Designed around real operational events.
Agent invoked
Risk threshold
Validation failed
Cost limit
What to measure
- Process cycle time
- SLA and deadline compliance
- Manual coordination hours
- Exception and error rate
- Revenue, margin or cost impact
Controls and human responsibility
- Role-based access to data and tools
- Human approval for high-risk or irreversible actions
- Complete audit trail from signal to verified result
Start with this domain
Start with one costly process.
Connect the systems involved, define the operating rule, measure the baseline and let COS close the loop. No rip-and-replace programme.