Architecture
Enterprise AI Architecture Hub
A collection of frameworks, principles, and architectural considerations for moving AI from experimentation into secure, scalable, and measurable enterprise systems.
Core Framework
Production AI Architecture Framework
A structured approach to evaluating and designing enterprise AI systems across eight critical dimensions.
Intelligence → Context → Systems → Security → Governance → Reliability → Economics → Outcomes
Explore the framework →Knowledge Domains
Enterprise AI Architecture
AI platforms, LLM applications, model orchestration, enterprise integration and production AI systems.
Agentic AI
Agent architecture, orchestration, tool use, human-in-the-loop systems, reliability and governance.
Enterprise RAG
Retrieval architecture, knowledge systems, hybrid search, evaluation, context engineering and enterprise data integration.
AI Governance & Security
Privacy, access control, data protection, auditability, evaluation, responsible AI and AI security architecture.
Cloud & Distributed Systems
AWS, scalable infrastructure, APIs, event-driven systems, reliability, observability and distributed architecture.
AI Economics
Inference optimization, model routing, caching, token economics, AI FinOps and cost-aware architecture.
Detailed publications for each domain are available in the Research section.