Case Study

Modernizing a Financial Institution: Bank-Grade Azure Foundation & AI Foundry

Executive Summary

We delivered a controlled operating environment with identity-first security, deterministic networking, and auditable controls for a regulated financial institution.

This engagement modernized cloud, identity, security, and governance foundations to support FFIEC / GLBA expectations. The work spanned strategy, architecture, hands-on implementation, and automation, with a clear emphasis on control-plane rigor, repeatability, and audit defensibility.

100%

Identity-Driven

FFIEC

Compliance Aligned

Zero

Implicit Trust

Audit

Ready & Defensible

The Challenge

The institution needed to modernize its platform while strictly adhering to regulatory expectations:

  • ✗Need for strong separation of duties across management, identity, and networking
  • ✗Requirement to eliminate ad-hoc sprawl and enforce policy-driven governance
  • ✗Transition from trust-based identity to policy-enforced access
  • ✗Secure enablement of GenAI workloads without weakening security posture

The Solution

We established a bank-grade Azure foundation aligned to Microsoft Enterprise-Scale Landing Zone (ESLZ) guidance.

The solution included a robust Entra ID governance model, a secure Hub-and-Spoke network architecture with Azure Virtual WAN, and a specialized AI Foundry landing zone for regulated AI workloads.

Architecture Overview

Secure, Scalable, and Compliant Foundation

MANAGEMENT & GOVERNANCEAzure PolicyRBACCost MgmtDefender for CloudIdentity PlatformEntra ID (Azure AD)Privileged Identity (PIM)Conditional AccessConnectivity HubAzure Virtual WANAzure Firewall Prem.ExpressRoute / VPNPrivate DNSApp WorkloadsAKS ClustersSQL & Cosmos DBAI FoundryAzure OpenAIAI Search & APIMAVD Host PoolsSecure Remote AccessFSLogix ProfilesOBSERVABILITYMicrosoft SentinelLog Analytics

The Outcome

  • ✓Identity is no longer “trust-based”; it is policy-enforced and auditable
  • ✓Network design favors deterministic routing and inspection
  • ✓Infrastructure changes are reviewable artifacts via IaC
  • ✓AI workloads enabled with private connectivity and full audit trails
  • ✓Audit questions can be answered with queries, not guesswork

“This is the difference between ‘we moved to Azure’ and ‘we can defend Azure to regulators.’”

Want the Technical Details?

Read the full case study for complete technical implementation details, including the 9 key workstreams and AI Foundry architecture.

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