RETRIEVAL AUGMENTED GENERATION IN PRODUCTION

Name: RETRIEVAL AUGMENTED GENERATION IN PRODUCTION
Brand: World Scientific Publishing Co Pte Ltd
Price: 180.99 AUD
Availability: PreOrder

Architecture, Patterns, And Runbooks

By: XU JUN

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Paperback | 21 September 2026

At a Glance

Paperback
436 Pages

Dimensions(cm)
22.86 x 15.24 x 3.0

Paperback

$180.99

or 4 interest-free payments of $45.25 with

Available: 21st September 2026

Preorder. Will ship when available.

This book is a practical, end-to-end guide to building product-implementation-ready Retrieval-Augmented Generation (RAG) systems for high-stakes domains such as healthcare, finance, education, legal services, and customer support. While Artificial Intelligence (AI) advances rapidly, Large Language Models (LLMs) continue to face challenges with factual consistency and domain-specific accuracy. LLM-based RAG systems address these limitations by integrating live, external knowledge sources to produce grounded, current, and trustworthy outputs.Readers are taken through the full RAG pipeline with MLOps/LLMOps — while tackling 30+ real-world implementation challenges, including data parsing & chunking, prompt rephrasing, retrieval quality, response synthesis, hallucination mitigation, evaluation frameworks, serving & monitoring enhancement, orchestration optimization, and graph-, tabular-, and agentic-RAG patterns. Clear architectures, case studies, and runnable code illustrate how to design, implement, validate, monitor, and scale robust RAG systems.The book also provides a balanced perspective on the current limitations of RAG approaches and their future potential as part of emerging agentic AI ecosystems. Whether you are an engineer, product leader, or researcher, this book equips you to deliver reliable, business-ready AI solutions while staying ahead of rapidly evolving technologies.All supplementary material (i.e. sample codes) are available at https://github.com/junxu-ai/RAG_Codes.

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