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Knowledge Graph Architectures: Designing Real-World AI Systems with Neo4j, Llms, and Rag for Semantic Search and Recommendation
Paperback
Publisher: Independently Published
Published: Oct 31 2025
Pages: 206
Weight: 0.54
Height: 0.44 Width: 5.50 Depth: 8.50
Language: English
From Concept to Deployment - Build AI Systems That Think in Context.
Artificial Intelligence is no longer just about models and data - it's about reasoning.
In a world dominated by large language models, the missing link is structure: the ability for AI to understand, connect, and recall knowledge intelligently.
Knowledge Graph Architectures is your complete guide to designing and deploying real-world AI systems powered by Neo4j, Graph Data Science, Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs).
Written by Robertto Tech, a seasoned AI systems engineer, this hands-on manual transforms abstract theory into concrete engineering blueprints for developers, data scientists, and architects.
What You'll Learn
✅ Graph Thinking for AI Systems - Understand how to model relationships, context, and semantics as the backbone of reasoning.
✅ Data Modeling for Semantic Search - Design flexible, schema-light structures that capture real-world intelligence.
✅ Cypher + Python Integration - Learn how to query, analyze, and automate your graphs with production-ready code.
✅ Embeddings and Hybrid Retrieval - Combine the power of vectors, graphs, and LLMs for state-of-the-art search and recommendation.
✅ Graph-Powered RAG Systems - Build retrieval-augmented generation pipelines that understand both structure and meaning.
✅ Graph Algorithms for Insight - Apply Neo4j Graph Data Science for fraud detection, recommendation, and community discovery.
✅ Deploying Graph-Based AI Apps - Architect scalable APIs and microservices that bring semantic reasoning to production.
✅ Future of AI Reasoning - Explore agentic AI, graph memory, and explainable intelligence for next-generation systems.
Who This Book Is For
AI Developers who want to integrate Neo4j and LLMs in real projects.
Solution Architects building scalable, reasoning-aware applications.
Data Engineers exploring hybrid retrieval and semantic graph pipelines.
Technical Leaders defining the architecture of cognitive AI systems.
Whether you're building an enterprise search engine, a personalized recommender, or an intelligent assistant, this book shows you how to architect the reasoning layer that turns AI into understanding.
Why It Stands Out
Hands-on projects with Neo4j, LangChain, and Python.
Instructor-style explanations that teach by doing.
Real-world diagrams, schema patterns, and best practices.
Designed for AI professionals who think in systems, not silos.
Knowledge Graph Architectures is more than a technical manual - it's a roadmap for engineers shaping the next wave of intelligent systems.
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