Productized advisory · 6 weeks fixed scope

AI Governance Foundation

Tested platform foundations for governing AI at scale in regulated multi-tenant Azure estates. Six weeks. Fixed scope. Named engineers.

Why this. Why now.

Large regulated multi-tenant orgs already run AI. Each business unit picks its own Cognitive Services, Azure OpenAI deployments, and ML workspaces. By the time the audit team asks "what AI runs where", nobody can answer in days. The EU AI Act high-risk obligations applied from August 2026. EMA and FDA released joint AI guiding principles in January 2026.

The Azure primitives exist (Microsoft Foundry hub, Azure ML registries, Purview AI Hub, Responsible AI Dashboard, Azure Policy). The gap is the assembly: how those primitives become a tenant pattern that BU teams adopt without slowing research, while satisfying audit-grade lineage and e-records integrity. That assembly is what we ship.

What you get in 6 weeks

Six concrete deliverables. Production-ready. Yours to keep.

Tenant pattern + IaC

Hub-spoke landing zone extension for AI workloads. Bicep or Terraform module that slots into your existing landing-zone pattern as a new tenancy type.

Central model registry

Azure ML registry deployed once at the org-tenant scope. Versioned, immutable, accessible across BUs. End-to-end lineage between training job, dataset, code, environment, and deployed endpoint.

Lineage + classification

Microsoft Purview connected to ML workspaces. Daily auto-publish of model and dataset metadata. AI Hub policies for classification, sensitivity labels, DLP, audit logging.

Stage gate pipelines

Azure DevOps or GitHub Actions YAML templates. Promotion from dev to test to prod gated by automated validation, RAI scorecard PDF, manual approval. Research workspaces stay unconstrained.

Audit-pack workbook

Azure Workbook with per-BU drill-down. Live model inventory, deployment state, scorecard status, data classification. Monthly export-to-PDF for audit responses.

Pharma overlay (when applicable)

GxP variant: high-risk decision tree (EU AI Act + MDR/IVDR triggers), ALCOA+ audit trail spec aligned to 21 CFR Part 11, context-of-use registration tied to model registry entry.

Who it is for

✓ Platform / Cloud Architecture leads at 5,000-plus-employee regulated orgs (pharma, finserv, energy, public sector).
✓ Orgs where multiple BUs run Azure AI today, with no central catalog and no Policy-level guardrails.
✓ Teams under audit pressure: EU AI Act, EMA/FDA joint AI principles, NIS2, DORA, ISO 42001, 21 CFR Part 11, GxP.
✓ Teams already running on Azure landing zones (Microsoft Foundry, Azure Verified Modules, or equivalent IaC pattern).

How it works

Six weeks. Named milestones. No ambiguity on what gets delivered when.

Wk 1

Tenant baseline

Inventory current AI workloads. Map to subscriptions, BUs, data classes, regulatory class. Gap report against landing-zone target.

Wk 2-3

Deploy + secure

Hub-spoke deployment. Entra group setup. Purview connection. Azure Policy guardrails (approved registry models, mandatory private endpoints, deny public endpoints, tag taxonomy).

Wk 4

Registry + pipelines

Registry contract. Promotion pipeline templates. RAI scorecard automation tied to gated promotions. Required-artifacts checklist enforced.

Wk 5

Audit pack

Audit-pack Workbook with per-BU view. Lineage query runbook. Compliance Manager template mapping (EU AI Act, ISO 42001, 21 CFR Part 11).

Wk 6

Pilot + handoff

Onboard one BU's AI workload end-to-end through the new pattern. Handoff session (4 hours live + recorded). Wiki documentation published in your ADO. 30-day async follow-up included.

What you leave with

Code in your repos. Documentation in your wiki. Patterns your platform team operates after we hand over.

Code + config

✓ Bicep or Terraform module for AI tenant pattern
✓ Azure Policy initiative (enterprise-grade) ready to deploy
✓ Promotion pipeline templates (ADO + GitHub Actions)
✓ Workbook JSON + KQL query library

Documentation + runbooks

✓ RAI scorecard generation runbook
✓ Lineage taxonomy + Purview classification rules
✓ Audit-response runbook (regulator question to answer in hours)
✓ Wiki documentation published in your ADO

What we do not do

We do not build custom models. We do not act as Data Protection Officer or file regulatory submissions on your behalf. We do not replace your existing SIEM, GRC, or cloud security tools; we integrate with them. We do not propose Microsoft AI Landing Zone verbatim where your enterprise agreement steers a different AI runtime; we adapt the pattern to what your platform team already owns.

Ready to scope your engagement?

Six weeks fixed scope, EU rate band. Reference price on request. Brief us on what your platform team owns today; we respond with a scoped quote.

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