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    <description>Chunking is the step most teams rush past when building RAG systems. The wrong chunking strategy makes your search retrieve the right document but the wrong passage — and the LLM hallucinates the rest. Here is what works.</description>
    <pubDate>Thu, 22 Jan 2026 00:00:00 GMT</pubDate>
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    <description>Pure vector search sounds like the obvious choice for RAG. In practice, it misses exact matches, product codes, and proper nouns that keyword search catches trivially. Hybrid search using RRF consistently outperforms either approach alone.</description>
    <pubDate>Thu, 05 Feb 2026 00:00:00 GMT</pubDate>
    <author>address@yoursite.com (NVN)</author>
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    <title>Vector Search on Azure: AI Search vs Cosmos DB vs PostgreSQL</title>
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    <description>Three Azure services now offer serious vector search capabilities. Azure AI Search, Cosmos DB for NoSQL, and Azure Database for PostgreSQL with pgvector each have a distinct sweet spot. Here is which to use and when.</description>
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