What we examine
- AI tools, agents, permissions, and data reach
- Owners, deployment approvals, logging, and review cadence
- Existing policies and how they map to configured controls
Engagement
Map deployed AI tools, permissions, and owners. Receive prioritized findings and a technical remediation scope.
The starting point
Policies can describe an intended state without explaining what deployed systems can actually do. An assessment connects governance expectations to technical reality.
Delivery depends on your systems, access, licensing, and agreed scope. Findings are not a certification of compliance, and a service description is not a guarantee of a particular outcome.
An AI governance assessment examines how AI is used and authorized in the actual environment. It reviews agents and applications, connected data, permissions, accountable owners, deployment processes, and evidence. The useful output is a prioritized set of findings linked to systems and decisions, with a clear path into remediation.
Bring a general description of the systems, the decision you need to resolve, the current stage of work, and the owners who can agree on access and scope. Establish a secure exchange process before sharing detailed architecture or sensitive records.
The agreed scope defines what will be delivered. For this engagement, the starting deliverables are:
Verification evidence, operating responsibilities, and unresolved dependencies should be clear before the work is handed over.