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ADVNT designs, builds and operates governed AI platforms that help people and organizations get useful work done.
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.
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 · PDFRun 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.
With an inventory in hand, the next decision is what governance actually has to own: models, data, agents, access and audit trail.
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 · PDFMap your policy onto a control architecture: where each rule is enforced, by which component, and what evidence it emits. Start from our published framework.
Compare your architecture against the three-layer model — intelligence, operating layer, applications — and check which layer each control is actually enforced at.
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 · PDFA/DVNT Services builds the internal function — intake, standards, review gates and the enablement to make them stick — rather than leaving governance with a vendor.
Equip the owning team with the same curriculum we run internally, so decisions are consistent across executives, engineers and operations.
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 · PDFA/DVNT Enterprise™ runs the operating layer that permissions, logs and evaluates every action — available A/DVNT-managed or customer-operated.
With evidence in place, the constraint is throughput. Advisory scopes the next set of use cases against the controls you already run.
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.
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.
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.
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.
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.
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.
Advisory scopes the decision; Assess, Govern, Architect and Enable build the capability; Enterprise licenses the governed runtime — all with published prices.