Productized engagement
AI Governance Foundation
A fixed-scope engagement that delivers a working platform pattern for governing AI workloads at scale in regulated multi-tenant Azure environments. Model registry, lineage, stage gates, audit workbook.
The problem
Large regulated organisations typically run AI before they have governed it. Each business unit picks its own Azure OpenAI endpoint, ML workspace, and Cognitive Services subscription. By the time the audit team asks what runs where, and on what data, the answer takes weeks to assemble.
The Azure primitives to fix this exist: Microsoft Foundry hub, Azure ML registries, Purview AI Hub, Azure Policy. The gap is the assembly: a tenant pattern that BU teams can adopt without slowing research, while producing the lineage and approval records that regulators expect.
What we deliver
This engagement delivers a working pattern, not a roadmap. We extend your existing Azure landing zone with an AI-specific spoke, deploy a central model registry at org-tenant scope, wire up Microsoft Purview for lineage and classification, build promotion pipelines that enforce gated handoff from dev to test to prod, and produce an audit-pack workbook your team can run against any regulator question.
- ✓ Hub-spoke landing zone extension, delivered as a Bicep or Terraform module that slots into your existing pattern.
- ✓ Central Azure ML registry deployed once at org-tenant scope: versioned, immutable, accessible across BUs with end-to-end lineage.
- ✓ Microsoft Purview connected to all ML workspaces, with daily auto-publish of model and dataset metadata, AI Hub policies, and sensitivity labels.
- ✓ Stage gate pipelines (ADO or GitHub Actions YAML) enforcing validated promotion from dev to test to prod. Research workspaces stay unconstrained.
- ✓ Audit-pack Azure Workbook with per-BU drill-down: model inventory, deployment state, data classification, monthly export for audit responses.
- ✓ Pharma overlay when applicable: GxP high-risk decision tree, ALCOA+ audit trail spec, context-of-use registration in the model registry.
Who this is for
Platform and cloud architecture leads in regulated organisations where multiple BUs run Azure AI today without a central catalog or policy-level guardrails. Teams that need to respond to a regulator question about their AI estate in hours rather than weeks. Organisations already running Azure landing zones who want to extend the pattern, not replace it.
Relevant regulatory context includes EU AI Act high-risk obligations (applied August 2026), EMA/FDA joint AI guiding principles (January 2026), ISO 42001, and GxP e-records requirements for pharmaceutical and medical device orgs.
Engagement milestones
Tenant baseline
Inventory current AI workloads. Map to subscriptions, BUs, data classes, regulatory category. Gap report against the landing-zone target state.
Deploy and secure
Hub-spoke deployment. Entra group setup. Purview connection. Azure Policy guardrails: approved registry models, mandatory private endpoints, tag taxonomy.
Registry and pipelines
Registry contract. Promotion pipeline templates. Automated validation tied to gated promotions. Required-artifacts checklist enforced on every merge.
Audit pack
Audit-pack Workbook with per-BU view. Lineage query runbook. Compliance Manager template mapping for EU AI Act, ISO 42001, and 21 CFR Part 11.
Pilot and 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 stays with you
Everything delivered goes into your repositories and your wiki. Your platform team operates it after handoff.
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 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 this engagement?
Brief us on your platform today. We respond with a scoped quote, named engineers, and a fixed price.