Four disciplines that keep enterprise AI governed end to end.
Engage on one, or all four in sequence — most clients start with intake and AUP, then layer in guardrails and PMO as the program matures.
Enterprise AI Incubation Security
Before an AI pilot reaches production, we review what it touches: which data it can access, which systems it connects to, and which vendors sit behind it. This is where most AI risk actually gets introduced — quietly, during the pilot phase, before anyone thinks to call it "in production."
We work directly with the teams running the pilot, not just security leadership, so controls get built in without stalling the project.
What you get
- Data access and exposure review for each AI pilot
- Vendor and model risk assessment
- Go/no-go security checklist before production rollout
- Recommendations sized to the pilot, not enterprise-wide policy
Acceptable Use Policy Development
An AUP only works if employees actually read and follow it. We write policies in plain language, scoped to the tools your organization actually uses, so the line between "approved," "restricted," and "needs review" is unambiguous.
Every policy is built to be enforced by the guardrails we implement next — not filed away as a document nobody references.
What you get
- Enterprise AI Acceptable Use Policy, drafted and reviewed with stakeholders
- Tool-by-tool approval tiers (approved / restricted / prohibited)
- Employee-facing rollout materials and training outline
- Exception and review-request process
AI Guardrails & Technical Controls
Policy without enforcement is a suggestion. We implement the technical and procedural controls that make your AUP real — access tiers by role, prompt and output monitoring where appropriate, logging, and clear escalation paths when something falls outside policy.
Controls are matched to actual risk level, so low-risk internal tools aren't over-engineered and high-risk, customer-facing systems aren't under-protected.
What you get
- Role-based access controls for AI tools and data
- Monitoring and logging design for AI system usage
- Escalation path for policy violations or edge cases
- Control documentation your IT team can maintain
Intake & PMO Establishment
Once policy and controls exist, the next AI use case needs the same rigor as the first — not a one-off exception. We stand up a standing intake process and the PMO structure to run it, so every new tool, model, or vendor gets reviewed on a consistent path.
This is what turns AI governance from a project into a program your organization can sustain without us.
What you get
- Standing AI use-case intake process and intake form
- PMO structure, ownership, and reporting cadence
- Review and approval workflow for new AI initiatives
- Handoff documentation for your team to run independently
Ready to scope your engagement?
Tell us where your AI program stands today and we'll recommend where to start.