Overview

Have you ever wondered why some AI systems feel truly intelligent while others only scratch the surface? Why do the most powerful AI applications understand relationships, not just raw data? And how do leading engineers design systems that reason, connect, and adapt in real time? This book was written to answer those exact questions. Mastering Neo4j for Graph-Powered AI is not a shallow tutorial or a collection of disconnected tricks. It is a complete, practical guide for developers, data professionals, and AI builders who want to move beyond flat tables and step into the world of relationship-aware intelligence. If you've ever struggled to model complex connections, scale intelligent systems, or extract deeper insights from your data, this book was written with you in mind. Do you want to build AI applications that understand context, not just keywords? Are you curious how modern knowledge graphs are powering smarter recommendation engines, fraud detection systems, search platforms, and decision engines? Have you heard about graph-enhanced AI and GraphRAG systems but don't know how to design or implement them correctly? This guide takes you step-by-step from core graph concepts to advanced, production-ready systems. You'll learn how to design efficient graph data models, write optimized queries, construct scalable knowledge graphs, and connect them directly to AI workflows. Instead of abstract theory, you will work with real-world scenarios, practical architectures, and clear implementation strategies that reflect how intelligent systems are actually built today. Inside this book, you will discover: How graph databases differ from traditional data systems and why they matter for AI How to design clean, scalable graph data models for real applications How to build and maintain powerful knowledge graphs How relationship-aware retrieval improves AI reasoning and accuracy How to engineer GraphRAG pipelines for smarter AI responses How to optimize performance, security, and scalability for production systems How graph analytics unlock insights that ordinary databases cannot reveal But more importantly, this book constantly asks you: What kind of AI do you want to build? One that stores data... or one that understands it? Whether you are a software developer, data engineer, AI practitioner, researcher, or tech entrepreneur, this guide will help you shift your mindset from data storage to relationship intelligence. You won't just learn how to use tools-you'll learn how to think in graphs, design for intelligence, and build systems that grow smarter as data grows richer. No vendor lock-in. No shallow walkthroughs. No hype without substance. Just a clear, structured path to mastering graph-powered AI systems with confidence and skill. If you are ready to stop building disconnected systems and start building truly intelligent, relationship-aware applications, this book is your next step.

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