Semantic Search

Semantic search is retrieval based on the meaning and intent behind a query, rather than exact keyword matching. It uses vector representations of text to find content that's conceptually related even when the actual wording is completely different.

Why it matters

Semantic search is the retrieval mechanism underneath most generative engines, which means repeating a target keyword phrase stops being the lever it once was. Content needs to comprehensively and clearly cover a concept in its own words, because the system is matching on meaning, not on a string.

Related terms

• Retrieval-Augmented Generation (RAG)

  Retrieval-Augmented Generation (RAG) is the architecture behind most AI search: the system retrieves a set of relevant documents or passages at query time, then generates its answer grounded in that retrieved material, rather than purely from what it learned during training.

• Conversational Search

  Conversational search is a natural-language search interaction where a user asks a question the way they'd ask a person, and receives one synthesized answer instead of a page of ranked links. It's the interface pattern behind ChatGPT, Perplexity, and Google's AI Mode.