What is query fan-out?

Query fan-out is the process by which AI search engines like ChatGPT search, Google AI Overviews, Perplexity, and Claude silently rewrite a single user query into multiple sub-queries. The engine runs those sub-queries in parallel, then synthesizes a single grounded answer from the combined results. To be cited, your page needs to answer several of those sub-queries, not just the seed.

How is this different from a keyword tool?

Keyword tools show what people type into Google. Fan-out shows what the AI engine asks itself before it writes the answer. Those sub-queries are usually longer, more specific, and question-shaped, and they're where AI citations are actually earned.

Are the sub-queries the real ones the engine runs?

They're a simulation. AI engines don't publish their internal fan-out. This tool uses an LLM to predict the sub-queries a fan-out step would generate for your seed. It's an accurate content brief, not a network trace.

How do I use the output?

Use the reformulations for on-page keyword coverage. Turn related questions into FAQ schema. Answer comparisons in a table. Cover adjacent topics in H2 sections. Mention the entity expansions in-context so the engine can ground its answer against your page.

Free tool

Free AI Search Query Fan-Out Tool

Free query fan-out simulator for generative search. When someone asks ChatGPT, Google AI Overviews, Perplexity, or Claude a question, each engine silently rewrites it into a fan of related sub-queries, retrieves passages for each one, then synthesizes a single answer. Enter any seed query and we predict those hidden sub-queries (informational, comparative, transactional, and long-tail), so you can build one page that answers the full fan-out and earns the citation.

Seed query

Works best with real search intent phrases. Avoid single words; use the same 4–8 word query you'd type into ChatGPT.

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