What are our people already putting into AI tools, and what stops sensitive data going with it?
We write the AI use rules and deploy guardrails that filter what goes into and comes out of your language models, so adoption does not outrun your data rules.
How it works: five steps, one Principal Engineer
One Principal Engineer leads it from the first call until your team has adopted the work and trusts it. Each step shows what it means for this engagement.
- Step 01
Discovery Call
30 minutes with the Principal Engineer who would lead this engagement. Free, and no sales handoff.
- Step 02
Direct Assessment
DiscoverWhat AI tools are in use and what data goes into them.
- Step 03
Shared Roadmap
WriteA short policy and approval model.
- Step 04
PE-Led Delivery
DeployGuardrails and monitoring.
- Step 05
Outcome Assurance
ReviewQuarterly review as tools change.
Ready when you are
Thirty minutes with the Principal Engineer who would lead the work. Pick a time on the spot, or email us.
What you get
- An AI use policy people can follow
- A governance model: who approves which uses, on which data
- Guardrails that filter prompts and responses for sensitive data
- Alignment with Purview labels, identity and access, and frameworks such as NIST AI RMF or ISO 42001
A Principal Engineer, not a salesperson
Likely lead: David Hyde-Volpe or David Frazer. You talk to the engineer who does the work on AI Governance & Guardrails.
Questions buyers ask
Will guardrails slow people down?
Good guardrails block the risky cases and let the rest through. We tune them with real usage.
Does this cover Microsoft Copilot?
Yes. Copilot shows people whatever they already have access to, so access cleanup and labels matter.
Which frameworks do you use?
We align to NIST AI RMF and ISO 42001 where useful, and keep the policy short.
More detail
AI that touches customer or regulated data needs rules and controls. We write the governance model and deploy guardrails that filter what goes into and comes out of your language models, so adoption does not outrun your data rules.
Related offerings
- Relevant
AI Readiness Assessment & Roadmap
"Which AI ideas will actually pay back here, and in what order?"
- Compliant
Sensitive Data Labeling & DLP (Microsoft Purview)
"Where do our sensitive files actually end up?"
- Secure
Identity & Access Security (MFA, SSO, Privileged Access)
"What could one stolen password reach?"
Not sure this is the right fit?
Take the blind spot check. Four questions to start, then go deeper on one dimension.
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