{"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—all while maintaining enterprise-grade security and compliance? Agentic Graph RAG guides technical leaders, engineers, and architects through the next evolution of generative AI. Combining retrieval-augmented generation (RAG) with graph-based reasoning and agentic capabilities, this guide provides a practical blueprint for building scalable, auditable, and intelligent AI 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 RAGImplement agents with dynamic memory, planning, and decision-making capabilitiesIntegrate knowledge graphs with large language models for robust, explainable AIDeploy scalable, governable multiagent systems ready for production environments","brand":"Gardners","offers":[{"title":"Default Title","offer_id":57513481929077,"sku":"9798341623170","price":63.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0612\/7193\/3106\/files\/9798341623170.jpg?v=1787220241","url":"https:\/\/backstory.london\/products\/agentic-graphrag","provider":"Backstory","version":"1.0","type":"link"}