What changes when enterprise AI moves beyond a pilot?
The challenge shifts from proving one useful task to operating it responsibly across people, systems, and changing conditions.
Read articleSolution area 03 / 05
Know what AI did, why, and where it needs attention.
Bring policies, evaluations, usage visibility, and audit review into the operating model for AI work.
The current problem
AI Control
Without clear oversight, teams cannot reliably investigate an output, improve a workflow, or decide when a system is ready to scale.
Use this solution as a focused starting point, then connect it to other platform areas as the process and governance needs become clear.
How it works
A clear path from task to outcome.
The final workflow, controls, and integrations are shaped around the customer's environment.
Observe agent and workflow activity
Review exceptions and evaluations
Improve instructions and controls
In practice
What this building block can support.
Capability areas
- Policy and guardrail design
- Activity and usage views
- Evaluations
- Audit and incident review
Illustrative uses
- Review a failed approval route
- Compare workflow quality over time
- Trace a model-assisted decision
The scope of monitoring, retention, and audit data must be agreed for each customer environment.
Discuss AI Control
Talk to us Start with a real process, then shape the right solution.
Tell us which work is slowing your team down and what systems are involved.