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AI is running across every function you own. You answer for all of it.
The CIO sits where AI adoption, operational risk, and accountability converge. Agents are now embedded across the estate you are responsible for, and you are the one asked whether it is governed, explainable, and safe. You cannot attest to what you cannot see.
Accountable for an estate you cannot fully see
AI has spread across every function I own, faster than I can inventory it.
The visibility problemCopilots, agents, and automations land in finance, operations, support, and engineering at once. The estate you are accountable for changes faster than any manual inventory can track.
→ Map maintains a live inventory of every agent, copilot, MCP and endpoint across the whole estate, discovered from real activity, including the deployments no one registered.
I am asked to attest that our AI is governed. Today that attestation rests on trust.
The attestation problemBoards and regulators increasingly want the CIO to stand behind AI governance. "We believe it is fine" is not an attestation a prudent officer wants to sign.
→ Continuous evidence, what ran, what was enforced, what was caught, turns attestation from belief into documentation.
Every business unit is buying and building AI. None of it is consistently governed.
The sprawl problemDecentralized AI adoption means dozens of tools and vendors, each with its own risk profile, and no common control layer across them.
→ One security layer across every agent, MCP and endpoint, wherever they run.
When something goes wrong, the question lands on my desk, without the evidence to answer it.
The accountability problemPersonal-accountability precedents (SolarWinds, Uber) raised the stakes for technology officers. When an AI incident hits, the CIO is expected to explain it.
→ Push-button reconstruction: a complete, ordered record of what any agent did, ready for the board, the regulator, or the incident review.
Governance you can stand behind
- Estate-wide inventory a live registry of every agent, copilot, MCP and endpoint across every function you own.
- Evidence-backed attestation continuous documentation, so what you sign is what the system proves.
- One security layer, everywhere consistent controls across decentralized AI adoption, on-device and in the cloud.
- Incident-grade reconstruction the full AI session, ready before the question reaches your desk.
- SaaS or on-premises deploy on Nexovern Cloud or inside your own infrastructure. Configurable hosting regions for data residency requirements.
Your first 30 days
The engagement is structured to produce a defensible result at each stage, starting with the question every framework asks first: what do you actually have running?
Days 0–5 · Discover
Runtime discovery across your estate. Output: a complete, risk-classified inventory of every agent in production, including the ones nobody registered.
Days 6–15 · Evidence
System-level telemetry live on your priority agents. Output: your first full incident-grade reconstruction, plus a gap report against the frameworks you answer to.
Days 16–30 · Enforce
Your highest-priority policies compiled into runtime gates, approval checkpoints, blast-radius limits, kill switches, with assurance reporting flowing to your committee.
Attest to your AI estate with evidence, not trust.
A demo maps the AI across your estate against the governance you are accountable for, and shows where the visibility gaps are.