Queue Inc. has released a free tool that visualizes the search query decomposition process "Query Fan-Out," which is executed internally by generative AI. It extracts the search queries actually used by Gemini and supports data-driven strategy formulation in AI search optimization (LLMO).
Queue Inc. Announces Free Release of "Query Fan-out Visualization Tool" on PR TIMES
A press release regarding the free release of the "Query Fan-out Visualization Tool," which visualizes the search query decomposition process executed internally by generative AI, has been published on PR TIMES.
Announcement of PR TIMES Publication
Queue Inc. officially released the "Query Fan-out Visualization Tool" on February 5, 2026, as part of its AI search optimization service "umoren.ai," and the details were formally distributed on PR TIMES.
This tool is the first initiative in the industry in Japan to extract and display actual search queries used internally by Gemini as real data.
Background: Generative AI is "Not Searching as Is"
Generative AIs like ChatGPT and Gemini do not search the user's question as is; instead, they go through a process called Query Fan-out, where the question is decomposed into multiple search queries for information gathering.
However, this decomposition process has become a black box,
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making it unclear which keywords will be cited by the AI
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and why competitors are being recommended
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leading to content creation based on guesswork
These challenges have arisen.
What is the Query Fan-out Visualization Tool?
With this tool, by simply entering a prompt,
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the search queries actually executed internally by Gemini
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the decomposed search intent
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and the referenced domain information
can be visualized.
The biggest feature is that it allows you to obtain actual search query data used by generative AI, not simulations.
Main Features
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Acquisition of executed fan-out queries
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Visualization of the decomposition structure of search intent
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Display of referenced domains
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Utilization for AI search optimization article design
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Data output in CSV format
This enables a transition from traditional "guess-based AI countermeasures" to "data-driven AI search optimization."
Expected Use Cases
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Identifying reasons why the company's services are not cited or mentioned in AI searches
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Analyzing which search queries competitors are being cited through
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Designing article titles and structures optimized for AI searches
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Verification of the effectiveness of LLMO (AI search optimization) measures
Future Developments
In the future, we plan to expand support to other models such as ChatGPT, and add features for correlation analysis between query fan-out and citation rates, among other enhancements.
Queue Inc. will promote an era where AI search measures are conducted based on "structure and data" rather than "intuition."
Service Overview
Tool Name: Query Fan-out Visualization Tool
Start Date: February 5, 2026
Price: Free
👉 Here is the article published on PR TIMES
https://prtimes.jp/main/html/rd/p/000000015.000147944.html
👉 Here is the tool page
https://umoren.ai/free-tools/query-fanout
Queue Inc. will continue to support companies in their information design in the era of generative AI.
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