Overview

Vector Databases & Embeddings in Practice is the definitive, production-focused guide to building real-world semantic AI systems. Go beyond theory and learn how to design, optimize, scale, and secure vector databases powering modern AI. From embeddings and ANN search to Retrieval-Augmented Generation, multimodal systems, agentic retrieval, and enterprise-scale deployment, this book delivers hands-on labs, architecture blueprints, case studies, and production checklists. If you build AI systems, RAG pipelines, search platforms, or enterprise knowledge copilots -- this is your blueprint. Build meaning. Engineer intelligence. Deploy with confidence.

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