Case Study

EIRA - Enterprise Multi-Tenant AI Platform

Multi-tenant enterprise AI platform with Microsoft Entra authentication, featuring 6 production AI services: Document QnA, General QnA, Internal QnA, Translation, MoM Extraction, and Image Generation.

Azure Kubernetes ServiceMicrosoft EntraAzure OpenAIMulti-tenantKEDASSO/IAMCost Optimization

Problem

Companies need AI assistance for daily operations but face challenges with data privacy, compliance, managing access across departments, and providing consistent AI capabilities while maintaining strict security boundaries.

Constraints

  • Multi-tenant platform with per-service cost visibility
  • Strict authorization across shared data sources via Microsoft Entra
  • Granular per-service per-user access control
  • Azure Kubernetes Service deployment with minimal standby resources

Key Design Decisions

Multi-tenant via Microsoft Entra

Single identity provider serving multiple business units with isolated data access and per-service per-user authorization.

Modular Microservices Architecture

Each AI feature deployed independently on AKS with independent scaling, reducing blast radius and enabling granular access control.

Shared Azure OpenAI with Cost Attribution

Centralized LLM access with rate limiting and per-tenant cost tracking, preventing usage sprawl while optimizing resource utilization.

Tradeoffs Accepted

  • Complex identity management across multiple business units
  • Increased operational surface area with granular access policies

Outcomes

  • Enabled enterprise-wide AI adoption with 100% data privacy compliance
  • Reduced manual meeting documentation by 70% through MoM extraction
  • Established reusable AI service patterns adopted across organization