Enterprise AI Factory inference hub Reference Design

• Governed Inference for the Enterprise AI Factory
  • The Fragmentation Problem
  • Drivers and Personas
• Enterprise AI Factory inference hub Reference Design
  • Portal
  • Gateway
  • Inference Backend
• Reference Design and Request Flow
  • Reference Design Scope
  • End-to-End Access and Request Flow
  • Developer Access
  • Gateway and Intelligent Routing
  • NVIDIA’s Model-Serving Approach
• Security, Governance, and Operations
  • Trust Boundaries and Governance Controls
  • Hybrid Routing and Serving Operations
  • Observability, Attribution, and Privacy
• Adoption Path
  • 1. Establish Governance and Portal Onboarding
  • 2. Introduce the Governed Gateway
  • 3. Operationalize Model Serving
  • 4. Add Hybrid Optimization
• NVIDIA Implementation Walkthrough
  • NVIDIA inference hub Walkthrough
  • Operating Lessons
• inference hub Reference Implementation
  • Reference Shape
  • Operating Invariants
  • Why This Matters
• Red Hat AI Factory with NVIDIA Reference Implementation
  • AI Gateway controls access, routing, and cost attribution for all model traffic
  • Inference Services run model workloads across engines and orchestration layers
  • Observability provides end-to-end visibility from prompt to token generation
  • Guardrails enforce safety policies on both user input and model output
  • Resource Orchestration manages GPU allocation across workloads
  • Platform
  • Extended AI Platform Services

Notices

• Notices
  • Notice
  • Trademarks
  • Copyright