Gen AI Leader Fundamentals of generative AI MEDIUM
PRODUCTION SCENARIO
A home-improvement retailer's site search returns nothing for “stop my faucet dripping” even though it sells washer kits described as “repairs leaking taps”. Product text and shopper queries rarely share the same words.

Which capability addresses this gap?

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Answer: Text embeddings, so search matches passages by meaning rather than exact words

Dense vector embeddings represent the meaning of text, so retrieval can surface passages that align with what a shopper asked even when the wording differs completely. Temperature and context length shape how a model generates, not how a search engine matches.
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