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Conceptual Redis Deep Dive: From Cache to AI Memory

Part 7: "Semantic Discovery" — Vector Embeddings and HNSW Graphs

Keyword search is failing. We introduce Redis Stack and RediSearch to build a "Find Similar Products" feature. We dive deep into vector embeddings, distance metrics (L2, Cosine), and how the Hierarchical Navigable Small World (HNSW) algorithm achieves logarithmic search times.

Conceptual Redis Deep Dive: From Cache to AI Memory

Part 8: "The Intelligent Agent" — Production RAG Architectures

Maya builds an AI shopping assistant. We move from naive retrieval to a production-grade Retrieval-Augmented Generation (RAG) system. We cover chunking strategies, hybrid search (combining vectors with metadata filters), and using Redis as conversational memory for LLMs.

© 2026 Titas Biswas

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