Retrieval-Augmented Generation in Action: Build Real-World Rag Pipelines with Langchain, Langgraph, and Agentic AI for Enterprise-Grade Knowledge Syst

By: Cordex, Finn

Unlock the full potential of Retrieval-Augmented Generation (RAG) and master the creation of advanced AI knowledge systems. This comprehensive guide takes you step-by-step from the foundational theory behind RAG to building production-ready pipelines using LangChain, LangGraph, and agentic AI architectures.

Whether you are an AI engineer, developer, or data scientist, you will learn to:

Design scalable RAG pipelines for enterprise-grade knowledge systems.

Integrate vector databases for efficient information retrieval.

Build agentic AI systems capable of reasoning across multimodal data.

Apply best practices for production-ready, fault-tolerant AI applications.

Packed with detailed Python examples, full implementation walkthroughs, and expert commentary, this book is your ultimate roadmap to mastering RAG in real-world environments.

• Format: Paperback
• Language: English
• ISBN: B0G1K4R2JF
• ISBN13: 9798273684188
• Release Date: November 2025
• Publisher: Independently Published
• Length: 258 Pages
• Weight: 0.67 lbs.
• Dimensions: 0.5" x 5.5" x 8.5"