Mastering Amazon Bedrock: Advanced Generative-AI Solutions with Foundation Models, Textract, RAG, Agents, and the AWS AI Suite

Audience: Software engineers, ML engineers, data scientists, cloud and solutions architects, and AI product leaders seeking to build production-grade generative-AI solutions on AWS. The book provides actionable patterns, reference architectures, and business-focused insights for teams modernizing document workflows, launching conversational agents, or embedding AI across enterprise platforms.

Description: Mastering Amazon Bedrock is the definitive, hands-on guide to designing, building, and operating production-grade generative-AI solutions on AWS. This book takes you beyond the basics, teaching you how to select, customize, and operationalize foundation models; extract rich insights from documents with Textract; build Retrieval-Augmented Generation (RAG) knowledge bases; orchestrate multi-step AI agents; and embed Bedrock into the broader AWS ecosystem—all while meeting enterprise-grade security, compliance, cost, and MLOps requirements. Through deep technical dives, annotated Python examples, and real-world case studies, you’ll gain the expertise to deliver scalable, responsible, and future-proof AI applications.

Table of Contents

Chapter 01: The Generative-AI Revolution on AWS: Why Bedrock Matters

Objective: Introduce readers to the transformative potential of generative AI for enterprises, the unique role of Amazon Bedrock, and the foundational journey ahead.

Sections:

Chapter 02: Amazon Bedrock Fundamentals: Architecture, Modes, and Getting Started

Objective: Equip readers with a foundational understanding of Bedrock’s architecture, operational modes, pricing, and essential concepts for building generative-AI applications, including hands-on onboarding guidance.

Sections: