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.
chapter01: The Generative-AI Revolution on AWS: Why Bedrock Matters
chapter02: Amazon Bedrock Fundamentals: Architecture, Modes, and Getting Started
chapter03: Foundation Models on Bedrock: Selection, Capabilities, and Use Cases
chapter04: Customizing and Evaluating Foundation Models: Fine-Tuning, Benchmarking, and Versioning
chapter05: Prompt Engineering, Caching, and Optimization for Bedrock
chapter06: Retrieval-Augmented Generation (RAG): Building Knowledge Bases with Bedrock
chapter07: Document Intelligence with Amazon Textract: Extraction, Processing, and Integration
chapter08: End-to-End Bedrock + Textract Solutions: Blueprints and Best Practices
chapter09: Agent Engineering and Orchestration: Designing Multi-Step AI Workflows
chapter10: Multimodal AI with AWS: Text, Vision, Speech, and Beyond
chapter11: Production Architecture and MLOps: Scaling, Deploying, and Operating Bedrock Solutions
chapter12: Responsible, Secure, and Compliant AI: Cost, Privacy, Guardrails, and Governance
chapter13: The Future of Generative AI on AWS: Trends, Innovations, and Emerging Tools
chapter14: Case Studies and Mini-Projects: Real-World Bedrock Solutions in Action