Architectures for the Intelligent AI-Ready Enterprise: Building real-world solutions with MongoDB

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Boris Bialek Sebastian Rojas Arbulu

Architectures for the Intelligent AI-Ready Enterprise

Building real-world solutions with MongoDB

Boris Bialek, Sebastian Rojas Arbulu, Taylor Hedgecock , Jim Scharf

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English

Packt Publishing Limited
05 September 2025

Enterprise software; Databases; Computer architecture & logic design

Create AI-ready enterprise solutions with MongoDB and discover how to design intelligent architectures that transform data into innovation, efficiency, and real business value

Key Features

Complete guide covering GenAI to agentic AI, semantic protection to multi-agent systems 25+ proven AI use cases delivering measurable impact across 6+ industries 15+ real enterprise case studies from Novo Nordisk, Base 39, and more Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionAI 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.

What you will learn

Design AI-ready data architectures that scale in production Define systems of action and explain why they matter for enterprises Modernize legacy systems for AI-ready, unified architectures Implement governance, privacy, and compliance frameworks for AI Explore real-world AI implementations for over six industries Deploy production RAG and agentic systems with MongoDB Apply semantic data protection in regulated industries Build domain-specific AI agents and intelligent copilots Apply MCP, causal AI, and multi-agent systems for future-ready architectures

Who this book is forThis book is for IT leaders, enterprise architects, solution designers, and innovators ready to transform AI potential into production reality. Whether you're modernizing legacy systems, implementing scalable AI solutions, or translating AI concepts into measurable business outcomes, this book provides practical frameworks and industry-proven patterns. Basic familiarity with enterprise systems and data architecture is helpful, but deep AI expertise isn't required.

By: Boris Bialek, Sebastian Rojas Arbulu, Taylor Hedgecock
Foreword by: Jim Scharf
Imprint: Packt Publishing Limited
Country of Publication: United Kingdom
Dimensions: Height: 235mm, Width: 191mm,
ISBN: 9781806117154
ISBN 10: 1806117150
Pages: 510
Publication Date: 05 September 2025
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Boris Bialek has worked in the IT industry since the 1990s and was one of the initial drivers of Linux in Europe, delivering the first SAP port to Linux, conducting the first benchmarks, and securing the first clients. Since then, he has led product and development teams across IBM and FIS, driving innovation for both the end product and development productivity. Boris Bialek joined MongoDB in 2019, igniting a focus on industry solutions based on MongoDB's document model. Promoted to global field CTO and VP of industries, he drives technical design. He works directly with numerous clients, helping them gain the benefits of the MongoDB Atlas data platform. Boris holds a master's in computer science from the Karlsruhe Institute of Technology. Sebastian Rojas Arbulu is an industry solutions specialist at MongoDB, where he collaborates with numerous stakeholders across diverse industries to help customers realize the transformative value of MongoDB through tailored, data-driven solutions, particularly for AI integration. Sebastian also leads his team's content strategy, including numerous additions such as blogs, white papers, magazines, and other thought leadership pieces. With a background in IT consulting, marketing, and digital transformation, among other areas, he has extensive experience in identifying customer needs and developing innovative solutions that prepare data for intelligent applications and unlock new possibilities. He holds a bachelor of business administration degree. Taylor Hedgecock is a strategic program leader and transformation partner who turns vision into velocity. With a career spanning startups to multinationals, she brings a mix of operational rigor, narrative clarity, and cross-functional orchestration. At MongoDB, she has led high-impact programs across AI, partner ecosystems, and services modernization, often serving as the connective tissue between vision and execution. Her work has guided C-level priorities, enabled go-to-market readiness, and driven large-scale change, establishing her as a trusted leader in aligning stakeholders, translating strategy into story, and driving outcomes that last. Taylor currently serves as senior program manager on the industry solutions team, partnering with ISVs and AI innovators to bring next-generation solutions to market. Previously, she was chief of staff for professional services leadership, where she helped launch new offerings and guided modernization strategy, shaping MongoDB's vision for applying AI to its hardest problems.