Enterprise AI Architecture & Governance

Why This Matters

Tools, models, and agents do not add up to a company capability. Governance, ownership, build-vs-buy, and an operating model are what make architecture survive contact with the enterprise.

Architecture Position

Enterprise Layer: systems, data, APIs, events, and governance wrapping the entire stack. See it on the architecture map.

Start Here

Building Enterprise AI Agents

Production harness: runtime, orchestration, tools, memory, RAG, security, observability, and production controls.

Advanced · 40 min

How LLMs Work — Complete Guide

End-to-end interactive visual overview of the entire LLM pipeline on one page.

Foundation · 45 min

Core Concepts

Architecture

Enterprise AI reference architecture
AI capability map
AI operating model
Architecture principles

Platform Strategy

Centralized vs federated
Build vs buy
Shared AI platforms
Vendor strategy

Integration

Enterprise APIs
Legacy systems
Data platforms
IAM
Event systems

Governance

Architecture governance
AI governance
Model governance
Data governance
Access governance

Risk

Risk classification
Security review
Privacy
Compliance

Organization

Platform teams
Product teams
Architecture ownership
Federated governance

Decisions

ADRs
Reference standards
Production readiness
Technical debt
Cost architecture

Advanced

Advanced material

Deeper guides for this domain are on the way.

Coming Soon

Architecture Patterns

Applied patterns for this domain live in the pattern library.

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Case Studies

Enterprise walkthroughs that apply this topic in a full system.

Browse case studies

Roadmaps

This topic appears in the Enterprise AI Architect path.

Follow the Enterprise AI Architect roadmap