Start with the mechanism.

One hour to choose the first governed AI question.

AI governance decisions are scattered across security, legal and the business, and the first technical engagement starts with three different expectations. In one hour we review the concern you bring and walk through the Microsoft options at a high level. You leave with one named decision owner and one scoped question for the first pilot. No access to your systems, no software, no fee.

Mechanism: In the hour we review the concern, discuss the Microsoft governance options at a high level and choose a single follow-up question.

Find the AI your people already use. Then decide, app by app.

Someone on your team pasted client work into an AI tool nobody approved, and you cannot name the tool. We read what your managed devices already know and get security, legal and the business to sign one app list. Then we test a scoped block in your change window, before anyone is surprised.

Mechanism: Collect the Cloud Discovery data and check which devices and people it actually covers.

Know what Copilot will find before your people do.

Microsoft 365 Copilot answers from what each person can already open, including the folders that were shared too widely years ago. We test the sharing and the labels first, scope a pilot group, and put the cleanup where the pilot proves it is needed.

Mechanism: Separate what was tested from what was assumed on one page.

Every agent with an owner, an identity and a gate.

Agents are arriving in your Microsoft 365 (your tenant) from Copilot Studio, Microsoft Foundry and vendors you did not choose. We inventory them in Microsoft Agent 365, give each one an owner and a permission row, and route consequential actions through a person.

Mechanism: Set the permission row: may see, may draft, may do with approval, may do alone.

Know which agent can act, on whose authority.

Agents are arriving from Copilot Studio, Microsoft Foundry and vendors you did not pick, and your name is on what they do. We inventory them, map each one's identity and data reach, and put an approval and evidence path around every consequential action.

Mechanism: Test the proposed action against policy and the caller's access.

Take one useful workflow from trial to controlled operation.

If the daily brief is wrong, the superintendent finds out on site and you find out from the owner. We take one useful workflow from trial to controlled operation with a baseline, a human approval point and failure recovery agreed before anything widens.

Mechanism: Define data access and an evaluation set using approved samples.

Turn Microsoft security signals into an owned response.

Show me the test, not the slide that says it was tested. Managed security here means Microsoft Defender and Microsoft Sentinel evidence leading to a triage decision. Containment happens under an authority you wrote down, and the evidence is filed the way your examiner expects.

Mechanism: Correlate evidence in Microsoft Defender XDR and Microsoft Sentinel.

Choose the AI boundary before choosing hardware.

You do not need to understand how the model works. You need to know what it can see, where it runs and who decided that. Managed Private AI chooses the boundary on the data rules before anyone chooses hardware, then runs a governed pilot inside it.

Mechanism: Compare tenant-private and local processing boundaries.

Someone has to run the agents after the pilot.

A pilot proves a workflow. Operations keep it inside its boundary month after month, when the people who built it have moved on. We run the agent estate on Microsoft Agent 365: inventory, access reviews, cost limits, incident handling and a monthly evidence pack your auditor can read.

Mechanism: Watch access, cost and drift against the agreed limits.

An AI engineer inside your Microsoft 365, owning the outcome.

Every proposal you see is phase one with a fixed price and phase two with a question mark. This one is a fixed sprint. A senior Simplicity IT engineer works inside your Microsoft environment with your team and takes one approved workflow from discovery to a working handover. The next phase is a decision you make after reading the first.

Find avoidable spend without weakening service.

You froze IT spending and the bill went up anyway. We read the Azure and Copilot lines before any commitment and give every line item an owner and an explanation. Each proposed change is shown with its saving and its service risk side by side.

Mechanism: Inspect utilization and resilience constraints.

Same playbook, every add-on.

Every vendor sells the deal team speed. The deal team needs proof: a Day 1 readiness record, a 100-day plan and a go or no-go in writing before anything connects, including the acquired company's agents, Copilot and shadow AI.

Mechanism: A Day 1 readiness record that separates tested from assumed.