Secure AI Activation gives you a defensible picture of every AI tool, agent, and model in your environment, and the governance to keep it that way as adoption accelerates.
Every department wants an AI pilot. Most already have one running, on a personal account, a vendor tool nobody scoped, or a model call buried in a workflow. Your risk register doesn't see it. Your auditors will.
Regulators have stopped asking whether you use AI. They're asking where, with what data, and how you prove it stays inside your compliance boundary. Without a current inventory, a data-handling policy, and a review process your people actually follow, every new model is a potential disclosure event waiting to surface during your next audit.
Pilots on personal accounts, unscoped vendor tools, and model calls inside workflows.
What each tool is allowed to touch, and what it can reach today regardless.
Who approves a new use case, on what criteria, and how the decision is recorded.
What you would hand an auditor asking where AI touches regulated data.
Copilot, ChatGPT Enterprise, and a few vendor-embedded agents are already live. Nobody can produce a single document that says what data they touch or who signed off.
A board member asked about AI risk. A customer sent a vendor questionnaire with 40 AI-governance questions. Your CEO wants a one-pager by Friday.
You're about to put a model into claims, clinical, or customer-facing workflow. You need to prove it's safe before it ships, not explain it after an incident.
Every output is something you can point to in a board meeting, hand to an auditor, or operationalize into your program.
Every tool, agent, and model in your environment, with data classification, ownership, and a risk score mapped to NIST AI RMF.
Roles, review gates, acceptable-use, and decision rights, written for your organization, not a template someone downloaded.
DLP, prompt/response logging, PHI and PII boundaries, and vendor-processing terms enforced at the tool and network layer.
The form, the reviewers, the SLAs, and the decision log, so the next AI request doesn't land in someone's inbox and die there.
One page your board can read, one appendix your audit committee can defend, and a set of metrics you'll actually report against.
What to fix this quarter, what to build next, and what to outsource, costed and sequenced against business value.
We harden the environment underneath every AI initiative: risk assessments and threat modeling, data classification and DLP, identity governance for AI tools, and shadow-AI discovery.
We stand up the program that keeps AI accountable: an acceptable-use policy, an approved tool catalog with vetting, data-handling standards, and an AI governance board.
We make AI usable by the people who actually do the work: role-based literacy training, department-level use case identification, and approved sandboxes by function.
NIST AI RMF, ISO 42001, HIPAA, and HITRUST mapped to your AI program, so one set of controls satisfies multiple audits.
See expertiseAgent identity, service-account hygiene, and human-in-the-loop approval gates for AI actions that touch regulated data.
See expertiseThe AI workloads live in your cloud. We make sure the surrounding network, secrets, and logging posture holds up to scrutiny.
See expertiseEvery prompt, response, and agent action captured, retained, and queryable, the evidence base an auditor will ask for first.
See expertiseWe'll map where you are, what's exposed, and what to do about it, no slideware.