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Descripción
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
Author: Anthony Alcaraz,Sam Julien
Publisher: O'Reilly Media
Published: 09/29/2026
Pages: 386
Binding Type: Paperback
Weight: 1.36lbs
Size: 9.19h x 7.00w x 0.80d
ISBN13: 9798341623170
BISAC Categories:
- Computers | Artificial Intelligence | Generative AI
- Computers | Software Development & Engineering | Systems Analysis & Desi
- Computers | Computer Architecture