What You'll Gain

• How RAG works end-to-end: chunking, embeddings, retrieval, and prompting
• Patterns for accuracy: grounding, citations, and evaluation
• Practical architectures for knowledge bases and enterprise search

Why Choose This Book

Many RAG systems fail due to poor chunking, weak retrieval, and missing evaluation. This book focuses on practical design decisions that improve accuracy and reliability.

Who Should Read This Book

Developers building internal knowledge assistants, document Q&A systems, or enterprise search with LLMs.

Outcome

Build RAG systems that answer with grounded context, better precision, and fewer hallucinations.