RAG Artificial Intelligence

Retrieval-Augmented Generation in Generative AI

Saloni Garg, Amit Sagtani, Kamal Kant Hiran

• Publisher: De Gruyter
• Year: 2026
• Print ISBN:
  9783112226773
• Edition: 1
• eBook ISBN:
  9783112226797
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

This book provides a deep dive into the foundations of RAG, covering transformer architectures, vector similarity search, and the integration of retrieval techniques into generative models. Readers will learn to implement RAG using open-source 
tools, explore real-world applications in chatbots, legal and medical document retrieval, and AI-assisted research, and address challenges like bias and misinformation. 

Table of contents

• Title Page
• Copyright
• Contents
• Frontmatter
• Contents
• Chapter 1 Introduction to Generative AI and RAG
• Chapter 2 Technical Foundations of RAG
• Chapter 3 Building Blocks of RAG Systems
• Chapter 4 Implementing RAG: Tools and Frameworks
• Chapter 5 Real-World Applications of RAG
• Chapter 6 Challenges and Ethical Considerations
• Chapter 7 Building and Implementing a Production RAG System
• Chapter 8 Future Trends in RAG and Generative AI
• Chapter 9 Integrating RAG with Large Language Models
• Chapter 10 Hybrid AI Architectures
• Chapter 11 Data Management in RAG Systems
• Chapter 12 Security and Robustness in RAG
• Chapter 13 Building Scalable Knowledge-Graph-Based RAG
• Chapter 14 RAG for Video Content Generation and Stock Production
• Chapter 15 The Role of Prompting in RAG and Generative AI
• Index
• Index