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Architectures for the Intelligent AI-Ready Enterprise

Architectures for the Intelligent AI-Ready Enterprise

By : Boris Bialek, Sebastian Rojas Arbulu, Taylor Hedgecock
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Architectures for the Intelligent AI-Ready Enterprise

Architectures for the Intelligent AI-Ready Enterprise

By: Boris Bialek, Sebastian Rojas Arbulu, Taylor Hedgecock

Overview of this book

AI is reshaping industries, yet most organizations struggle to scale beyond pilots. Architectures for the Intelligent AI-Ready Enterprise bridges this gap with practical frameworks for building AI-ready architectures that deliver lasting business value. The book helps you explore System of Action databases and see why they're revolutionizing real-time decision-making. Through real-world applications across industries, from manufacturing and healthcare to financial services and retail, you'll discover how leading organizations transform their operations. You'll learn semantic data protection techniques that enable AI in regulated industries, as well as master advanced patterns including agentic AI and multi-agent orchestration. Written by MongoDB and industry practitioners, this book combines strategy with technical depth and proven business value. You’ll modernize by enabling AI innovation while preserving existing investments, implement trustworthy AI with governance frameworks, and build scalable solutions using a unified data platform like MongoDB that delivers measurable ROI and transformation. Whether you're architecting next-generation systems or modernizing legacy infrastructure, this book provides the patterns, case studies, and expert guidance to build enterprises that’ll thrive in an intelligent future.
Table of Contents (26 chapters)
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1
Part 1: AI and Key Concepts
7
Part 2: Real-World Case Studies and Implementations
19
Part 3: The Future of Intelligent Enterprise
24
Index
25
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Afterword

As we write this, we’re struck by how far this project has come since it was first suggested that we turn our scattered industry insights into a cohesive guide. What began as an effort to organize our existing knowledge has evolved into something we never expected: a comprehensive framework that bridges the gap between AI theory and production reality.

The process of writing also changed how we saw our own experiences. What began as documenting case studies soon turned into recognizing the deeper forces at play. We realized that decisions about data, governance, and system design consistently shaped outcomes. Rather than a set of disconnected stories, the chapters revealed a bigger picture. The real breakthroughs came from aligning technology choices with business realities.

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