AI search engine

An AI search engine answers a user's query by retrieving relevant web sources and synthesising a cited answer with a language model — the category that includes Perplexity, ChatGPT Search, Claude with web, and Gemini AI Overviews.

AI search engines (sometimes called answer engines) replaced the "list of links" with "synthesised cited answer" in 2025-2026. The pipeline: query rewriting, web search (sometimes proprietary index, sometimes Bing or Google), retrieval of top documents, synthesis with citations by a strong LLM. Major players: Perplexity, ChatGPT Search, Claude with web, Gemini AI Overviews, You.com, Brave Leo, Phind. For content publishers, ranking in AI search citations is the new SEO frontier — see <a href="/llms.txt">llms.txt</a> and our schema upgrades on this site for one example of the publisher-side response.

Common mistakes

• Treating AI search engines as a single audience — each one has its own crawler, ranking, and citation behaviour.
• Ignoring AI search citations in publisher analytics — they convert differently from organic search.

FAQ

Related terms

• Retrieval-augmented generation (RAG) — Retrieval-augmented generation (RAG) injects relevant documents into the prompt at query time so the model answers from your data instead of its training memory.
• Grounding — Grounding is any technique that ties a language model's output to verifiable sources — retrieved documents, tool results, structured data — instead of pure memory.
• Semantic search — Semantic search finds documents by meaning rather than keyword match, using embedding similarity in a vector space.
• Embeddings — Embeddings are dense numeric vectors that represent the meaning of text, images, or other data, allowing similarity to be measured as vector distance.

Last updated: 2026-06-01. Raw markdown: https://promtable.com/glossary/ai-search-engine.md.