{"product_id":"agentic-graphrag","title":"Agentic GraphRAG","description":"What if your AI systems could retrieve information, reason over complex knowledge, plan actions, and continuously learn--with enterprise-grade security and compliance? Agentic GraphRAG guides technical leaders, engineers, and architects through the next evolution of GenAI. Combining retrieval-augmented generation (RAG) with graph-based reasoning and agentic capabilities, this guide is a blueprint for building scalable, auditable, intelligent systems. Written by Anthony Alcaraz and Sam Julien, this book demystifies knowledge graphs, graph memory, neural-symbolic reasoning, and agent orchestration through real-world case studies, hands-on design patterns, and production-ready architectures. Readers will learn how to construct graph-native retrieval systems, integrate advanced reasoning into agent workflows, and address enterprise challenges around governance, scalability, and transparency.  - Design graph-augmented architectures that surpass traditional RAG - Implement agents with dynamic memory, planning, and decision-making capabilities - Integrate knowledge graphs with LLMs - Deploy scalable, governable multi-agent systems ready for production environments","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":57628743926086,"sku":"9798341623170","price":64.3,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0852\/3081\/3510\/files\/af3bf1a36a9b492050b0ec3a7d543b4256c6140f96b4664274ab0c91c652db00.jpg?v=1792218701","url":"https:\/\/www.averdo.com\/products\/agentic-graphrag","provider":"Averdo","version":"1.0","type":"link"}