A/DVNT Enterprise™ — the AI Governance and Operating Layer for Claude · live in under 60 minutes
    Guides · Govern itDecision tree

    Four questions decide
    how you govern AI.

    Governance is not a document — it is a set of decisions about inventory, architecture, ownership and evidence. Answer each question honestly and follow the branch to the content or offer that closes that gap.

    Answer in order.
    Stop at your first no.

    0 / 4 answered
    1. Q1

      Do you know what AI is already running inside the business?

      Governance starts with an inventory. Shadow tooling, unlogged prompts and ungoverned data paths are the first thing any auditor asks about.

      Download the checklistAI Inventory Checklist · PDF
      Start with a posture read.

      Run the open diagnostic first. You get a posture score, a mapped risk surface and a 30/60/90 plan before you commit budget to any control framework.

      Move to the definition.

      With an inventory in hand, the next decision is what governance actually has to own: models, data, agents, access and audit trail.

    2. Q2

      Is your governance written down as an architecture, or as a policy?

      A policy document does not stop an ungoverned call. Controls have to live in the runtime — permissioning, logging and evaluation at the layer the models run on.

      Download the checklistGovernance Architecture Checklist · PDF
      You need a reference architecture.

      Map your policy onto a control architecture: where each rule is enforced, by which component, and what evidence it emits. Start from our published framework.

      Pressure-test the model.

      Compare your architecture against the three-layer model — intelligence, operating layer, applications — and check which layer each control is actually enforced at.

    3. Q3

      Who inside the business owns AI decisions day to day?

      Governance without an owner decays inside a quarter. Someone has to run intake, approve use cases, and hold the standards as teams scale.

      Download the checklistAI Ownership & Governance Checklist · PDF
      Stand up a Centre of Excellence.

      A/DVNT Services builds the internal function — intake, standards, review gates and the enablement to make them stick — rather than leaving governance with a vendor.

      Give them the standard.

      Equip the owning team with the same curriculum we run internally, so decisions are consistent across executives, engineers and operations.

    4. Q4

      Can you produce an audit trail for every AI action, today?

      This is the question that decides whether AI reaches production in a regulated environment. If the answer is no, the runtime is the gap — not the policy.

      Download the checklistAI Audit Trail Checklist · PDF
      Operate on a governed runtime.

      A/DVNT Enterprise™ runs the operating layer that permissions, logs and evaluates every action — available A/DVNT-managed or customer-operated.

      Then scope the next build.

      With evidence in place, the constraint is throughput. Advisory scopes the next set of use cases against the controls you already run.

    Governance needs an owner.
    That is ADVNT Services.

    A/DVNT Services is the function that runs intake, sets standards, holds review gates and enables the teams shipping against them. It sits between the architecture (what the controls are) and the runtime (where they are enforced) — from $85K.

    Short answers,
    with somewhere to go next.

    What is AI governance, in practical terms?

    It is the set of controls that decide which models run, on what data, for whom, and with what evidence. In practice it is permissioning, logging and evaluation enforced in the runtime — not a policy document sitting beside it.

    Where do we start if we have no inventory?

    With a diagnostic. The open AI Audit maps what is already running, scores your posture and returns a 30/60/90 plan, so the first governance spend is aimed at a real gap rather than a guess.

    Do we need a Centre of Excellence, or is a policy enough?

    A policy without an owner decays inside a quarter. A/DVNT Services stands up the internal function — intake, standards, review gates and enablement — so governance decisions keep being made after the consultants leave.

    How is governance enforced at runtime?

    Through the AI operating layer: every action is permissioned, logged and evaluated before it reaches a model or a system of record. A/DVNT Enterprise™ runs that layer A/DVNT-managed or customer-operated.

    How do we choose a partner for this?

    Judge on evidence, not decks: who owns the architecture, where the controls are enforced, what audit trail you keep, and whether your team can run it without them.

    The AI Governance & Operating SystemGovern · Operate · Transform

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    One system to govern, orchestrate, and transform — across every team and industry.

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