Start with what your organization wants to achieve. Establish the control baseline, reveal actual AI use and turn the findings into an achievable plan.
Bring your control environment and actual AI use into one conversation. Turn what we learn into a practical, risk-based roadmap for the AI you build and consume.
Assess applicable security controls against MITRE SAFE-AI, complemented by governance criteria. Establish what is documented, implemented and supported by evidence.
Discover approved and shadow AI across the agreed scope. Identify applications, models, agents, connectors, data exposure and activity. Make coverage limits visible.
Combine context and evidence. Assess use-case risk, select proportionate controls and define the path toward an AI control plane.
The three pillars establish the baseline, evidence and roadmap. This six-step lifecycle connects them to implementation and ongoing assurance.
Identify AI uses, owners, data and connections. Record visibility gaps.
Evaluate consequences and authority. Assign a justified use-case risk tier.
Define required safeguards, shared responsibilities and justified exclusions.
Apply agreed controls across identities, gateways, pipelines and operations.
Test effectiveness. Remediate, restrict, accept residual risk or stop.
Track activity, performance and changes. Reassess and verify remediation.
Start with your use cases, priorities and existing controls. We’ll help define a practical assessment scope.
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