Overview

Modern AI systems don't fail because they lack intelligence they fail because they lack structure, context, and reasoning. Large Language Models (LLMs) are powerful, but without grounding, they can produce hallucinations, inconsistent outputs, and shallow reasoning. To build truly reliable AI systems, you need more than prompts you need a structured representation of knowledge. That's where knowledge graphs come in. Knowledge Graph Engineering for AI Systems by Clifford Nexon is a comprehensive, hands-on guide to designing, building, and integrating knowledge graphs with LLMs to create accurate, explainable, and production-grade AI applications. This book goes beyond theory and introduces a systems-level approach to combining structured and unstructured data turning disconnected information into a connected intelligence layer that powers smarter AI.

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