Category: Semantic Search

  • Enterprise-Grade RAG on Azure

    Enterprise-Grade RAG on Azure

    โœ๏ธ ๐๐ฒ ๐€๐›๐ก๐ข๐ฌ๐ก๐ž๐ค ๐Š๐ฎ๐ฆ๐š๐ซ | #๐…๐ข๐ซ๐ฌ๐ญ๐‚๐ซ๐š๐ณ๐ฒ๐ƒ๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ž๐ซ โญ Why Every Enterprise Needs RAG Today Modern enterprises generate massive unstructured data: Most of this data remains locked, making organizations slow, dependent on SMEs, error-prone, and high-cost. A Retrieval-Augmented Generation (RAG) system solves this by: Azure provides the most robust platform to build secure, compliant, scalable enterprise RAG.…

  • How Search Works in Vector Databases โ€“ From โ€œTop Gunโ€ to โ€œMaverickโ€

    How Search Works in Vector Databases โ€“ From โ€œTop Gunโ€ to โ€œMaverickโ€

    โœ๏ธ ๐๐ฒ ๐€๐›๐ก๐ข๐ฌ๐ก๐ž๐ค ๐Š๐ฎ๐ฆ๐š๐ซ | #๐…๐ข๐ซ๐ฌ๐ญ๐‚๐ซ๐š๐ณ๐ฒ๐ƒ๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ž๐ซ ๐Ÿง  Why Do We Need Vector Databases? Traditional databases store structured data (rows & columns) and perform keyword or pattern matching.But AI systems donโ€™t think in keywords โ€” they think in meanings. For example: Thatโ€™s why modern AI systems like ChatGPT, RAG pipelines, and semantic search engines rely on…