5 Guides

Architecture

Reference architectures for building production AI systems—from enterprise RAG and GraphRAG to knowledge graph platforms and modern LLM applications.

These guides explain how production AI systems are designed, including retrieval pipelines, knowledge graphs, LLM integration, AI agents, governance, scalability, observability, and enterprise deployment patterns.

These guides assume familiarity with AI Fundamentals, LLM Concepts, Retrieval & Search, Knowledge Graphs, and AI Agents, and show how these capabilities combine into production AI systems.

Core Architecture

AI System Architecture
Reference architecture for modern enterprise AI systems, bringing together retrieval, knowledge graphs, AI agents, LLM gateways, caching, observability, security, and production deployment.

Retrieval Systems

Enterprise RAG Architecture
Production RAG architecture — hybrid retrieval, ACL filters, model routing, caching, guardrails, and observability for multi-tenant enterprise systems.
GraphRAG Architecture
Reference architecture for graph construction, community detection, hybrid retrieval, graph traversal, and query planning.

Knowledge Graph Systems

Knowledge Graph + LLM Architecture
Reference architecture for grounding, entity resolution, graph traversal, hybrid reasoning, and structured retrieval with LLMs.
Enterprise Knowledge Graph Architecture
Reference architecture for ontology governance, RDF, OWL, SHACL, ingestion, semantic integration, and enterprise data architecture.