# What is query fan-out?

> The plain-English definition, where Google, OpenAI, Anthropic, Perplexity and others describe it in their own docs, and what it changes for a business that wants to be cited.

Updated October 6, 2026 · AI Syndicate team · https://www.aisyndicate.com/glossary/query-fan-out/

**Quick answer:** **Query fan-out** is when an AI engine splits one question into several smaller searches, runs them, and blends the results into one answer. Google says AI Overviews and AI Mode do it. OpenAI, Anthropic, Google's Gemini, Perplexity and xAI describe similar multi-search behavior in their docs. Your page can be cited for a sub-question you never targeted.

**Our take:** Write for the follow-up questions, not just the headline keyword. Google, OpenAI, Anthropic and Perplexity all say their AI can run several searches for one prompt. Each of those smaller searches is another chance for a page to be picked. A page that only answers the main question competes once. A page that also answers price, timing, risks and comparisons competes several times inside the same answer.

## What are the key facts about query fan-out?

| Engine | What its maker says | Source |
| --- | --- | --- |
| Google AI Overviews and AI Mode | Both "may use a 'query fan-out' technique", issuing multiple related searches across subtopics and data sources | Google Search Central |
| Google AI Mode | Breaks a question into subtopics and issues "a multitude of queries simultaneously" (May 2025) | Google |
| Google Deep Search | Uses the same technique and "can issue hundreds of searches" | Google |
| Gemini (API) | The model "automatically generates one or multiple search queries and executes them" | Google AI for Developers |
| Gemini Deep Research | Turns a prompt into a "multi-point research plan", then searches and browses the web | Google |
| OpenAI (API) | Reasoning models can search, read results and "decide whether to keep searching"; deep research often taps "hundreds of sources" | OpenAI |
| Claude (API) | Searches "can repeat multiple times" in one request; simple questions use 1 to 3 searches, research 10 or more | Anthropic |
| Perplexity (Agent API) | Research presets allow up to 15 steps of "multi-step research"; the top preset allows 100 | Perplexity |
| Grok (API) | "The model may call multiple tools to answer a query" and continues until it has enough | xAI |

## What does query fan-out mean in plain English?

When you type one question into an AI engine, it often doesn't run just one search. It works out what you'd need to know to get a good answer, searches for each of those pieces, reads the results, and writes one answer from all of them.

Here's a made-up example to show the idea. Someone asks: "Is it worth replacing my roof this year?" An engine that fans out might look up several things at once:

- typical roof replacement cost in their area
- signs a roof needs replacing rather than repair
- how long different roofing materials last
- whether insurance covers roof replacement
- the best time of year to replace a roof

The person never typed any of those. The engine did. Then it might cite a different page for each part of the answer.

Google gives a real example of the counting in its Gemini docs: a single prompt might lead the model to search both "UEFA Euro 2024 winner" and "Spain vs England Euro 2024 final score," and Google counts that as two searches. [Google AI for Developers](https://ai.google.dev/gemini-api/docs/google-search)

## Which AI engines use query fan-out?

Google is the only company that uses the name "query fan-out" in its official docs. Several others describe the same idea in their own words.

**Google AI Overviews and AI Mode.** Google's page for site owners says both features "may use a 'query fan-out' technique — issuing multiple related searches across subtopics and data sources — to develop a response." Google adds that this helps them show "a wider and more diverse set of helpful links" than regular search results. [Google Search Central](https://developers.google.com/search/docs/appearance/ai-features)

**Google AI Mode and Deep Search.** In a May 2025 post, Google said AI Mode breaks your question "into subtopics" and issues many queries at once on your behalf. Deep Search uses the same technique "taken to the next level" and "can issue hundreds of searches." [Google](https://blog.google/products/search/google-search-ai-mode-update/)

**Gemini.** Google's developer docs say that, when needed, Gemini "automatically generates one or multiple search queries and executes them." [Google AI for Developers](https://ai.google.dev/gemini-api/docs/google-search) Gemini Deep Research goes further: it turns your prompt into a "multi-point research plan," then looks for missing information and gaps based on what it has already found. [Google](https://gemini.google/overview/deep-research/)

**OpenAI (the maker of ChatGPT).** OpenAI's developer docs describe "agentic search," where a reasoning model searches as part of its thinking, looks at the results and decides "whether to keep searching." Its deep research mode searches as it goes, "often tapping into hundreds of sources." [OpenAI](https://developers.openai.com/api/docs/guides/tools-web-search)

**Claude.** Anthropic's docs say that during one request, searching "can repeat multiple times." Anthropic adds that simple factual questions typically use 1 to 3 searches, while comparisons or research across several businesses or products "can use 10 or more." [Anthropic](https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool)

**Perplexity.** Perplexity's Agent API has presets for different depths. Its "medium" preset is described as "In-depth, multi-step research" with up to 15 steps, and its most open-ended preset allows up to 100. [Perplexity](https://docs.perplexity.ai/docs/agent-api/presets)

**Grok.** xAI's docs say Grok works out what information it needs, and "the model may call multiple tools to answer a query," repeating until it has enough. [xAI](https://docs.x.ai/docs/guides/tools/overview)

> **One caution:** most of these are developer docs, not a description of the consumer apps. They show the engines are built to run several searches per question. How many searches each app runs for your customers' questions isn't published.

## Why does query fan-out matter for my business?

Because the searches that decide who gets cited aren't always the ones your customer typed.

- **You can be cited for questions you never targeted.** If an engine looks up "how long does a metal roof last" while answering a bigger roofing question, a clear page on that one point can earn a link in the final answer.
- **More pages get a chance.** Google says fan-out lets its AI features show a wider and more diverse set of links than regular search. [Google Search Central](https://developers.google.com/search/docs/appearance/ai-features) That's room for a smaller business, not only the top few results.
- **Ranking for the main keyword isn't the whole job.** The final answer is built from several searches, so a competitor who answers the side questions well can show up even if you rank higher for the main one.
- **The basics still apply.** Google says there are no extra technical requirements to appear in AI Overviews or AI Mode. A page needs to be indexed and eligible to show in Search with a snippet. [Google Search Central](https://developers.google.com/search/docs/appearance/ai-features)

## How do I optimize my pages for query fan-out?

This section is our advice. No AI company publishes a list of the sub-searches it runs, so these steps are about covering the likely ones well.

1. **List the follow-up questions.** For each service or product, write down what a careful buyer would also want to know: cost, timing, risks, alternatives, "is it worth it," and what to ask before hiring. Those are the side searches an engine is likely to make.
2. **Answer each one clearly on your site.** Give every important follow-up its own short section with a question as the heading and a direct answer in the first sentence or two. Big topics can get their own page.
3. **Use real, specific facts.** Price ranges you actually charge, how long jobs really take, the areas you serve. A vague answer gives an engine nothing worth quoting.
4. **Link related answers together.** Connect your main service page to the pages that answer its follow-ups, so a reader, and a crawler, can move between them.
5. **Keep each page findable.** Make sure the pages are indexed and that you aren't blocking the AI crawlers you want. Google's AI features need indexing and snippet eligibility, and nothing more.
6. **Don't write a page for every possible phrasing.** Fan-out is about covering real sub-topics, not making dozens of thin pages that say the same thing in slightly different words.

## How can I see query fan-out happening?

Ask an AI engine a broad question your customers ask, then look at the sources it cites. You'll often see links to pages about narrower points than your question. Those narrower points are clues to what the engine searched for.

Our [Prompt Simulator](/prompt-simulator/) runs one question across 12 engines at once and shows which sources each one cites, so you can see which side questions your competitors are winning. For the related idea of how AI looks things up before it answers, see [retrieval-augmented generation](/glossary/retrieval-augmented-generation/).

## FAQ

### Is query fan-out the same as retrieval-augmented generation (RAG)?

No, but they're related. RAG means an AI looks things up before it answers. Query fan-out is one way of doing the looking up: splitting the question into several searches instead of one. See [retrieval-augmented generation](/glossary/retrieval-augmented-generation/).

### Does ChatGPT use query fan-out?

OpenAI doesn't use that name, but its developer docs describe models that search, check the results and decide whether to keep searching, and a deep research mode that often taps hundreds of sources. [OpenAI](https://developers.openai.com/api/docs/guides/tools-web-search)

### How many searches does Google's AI Mode run?

Google hasn't published a fixed number. It says AI Mode issues "a multitude of queries simultaneously," and that Deep Search "can issue hundreds of searches." [Google](https://blog.google/products/search/google-search-ai-mode-update/)

### Do I need special markup to be picked up in fan-out searches?

No. Google says there are no additional technical requirements to appear in AI Overviews or AI Mode: a page needs to be indexed and eligible to show in Search with a snippet. [Google Search Central](https://developers.google.com/search/docs/appearance/ai-features)

### Can I see the exact sub-searches an AI engine ran?

Usually not in the consumer apps. Developers can: Gemini's API returns the queries it ran, and Claude's API shows each search query in its response. [Google AI for Developers](https://ai.google.dev/gemini-api/docs/google-search) [Anthropic](https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool)

## Sources

1. [AI features and your website](https://developers.google.com/search/docs/appearance/ai-features) — Google Search Central. Read Oct 6, 2026.
2. [AI in Search: Going beyond information to intelligence](https://blog.google/products/search/google-search-ai-mode-update/) — Google. Read Oct 6, 2026.
3. [Grounding with Google Search](https://ai.google.dev/gemini-api/docs/google-search) — Google AI for Developers. Read Oct 6, 2026.
4. [Gemini Deep Research](https://gemini.google/overview/deep-research/) — Google. Read Oct 6, 2026.
5. [Web search](https://developers.openai.com/api/docs/guides/tools-web-search) — OpenAI. Read Oct 6, 2026.
6. [Web search tool](https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool) — Anthropic. Read Oct 6, 2026.
7. [Agent API presets](https://docs.perplexity.ai/docs/agent-api/presets) — Perplexity. Read Oct 6, 2026.
8. [Tools overview](https://docs.x.ai/docs/guides/tools/overview) — xAI. Read Oct 6, 2026.