Learn how MongoDB helps organizations build scalable, secure, and AI-ready data foundations that power RAG, AI agents, and intelligent applications while simplifying performance, governance, and growth. Key Features Identify the data requirements that enable AI applications to succeed in production Evaluate retrieval strategies for accurate and trustworthy AI experiences Apply architectural principles for scalable, AI-ready data platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAI success depends on more than models, it requires a data foundation built for scale, intelligence, and trust. In Future-Ready Data Foundation with MongoDB, you’ll discover the principles behind building AI-ready data architectures that support modern applications, retrieval-augmented generation (RAG), and AI agents. This concise guide explores the critical role of data in AI modernization and shows how MongoDB helps organizations create a unified foundation for innovation. Through practical architectural insights, you’ll learn how retrieval strategies influence the quality and reliability of AI outcomes and how MongoDB’s document model and vector search capabilities support intelligent data access. You’ll also explore the scalability, performance, and operational patterns required to keep AI systems running efficiently, including replication, sharding, workload isolation, and search optimization. Finally, you’ll examine the governance, observability, security, and compliance considerations that help organizations deploy AI responsibly and at scale. By the end of this book, you’ll be equipped to evaluate, design, and optimize data foundations that support the next generation of AI-powered applications.What you will learn Identify the data foundations required for successful AI initiatives Compare lexical, vector, and hybrid retrieval strategies Understand how RAG and AI agents shape modern AI architectures Use MongoDB's document model to store and manag
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