umoren.ai on PR TIMES | Free LLM Visualization Analysis Tool

A press release on the free launch of the LLM Visualization Analysis Tool—which quantifies how often a company is cited and recommended in AI search—has been published on PR TIMES.

PR TIMES Publication Notice

On January 28, 2026, Queue released a free tool called “LLM Visualization Analysis Tool” as part of its AI search optimization service umoren.ai. The tool shows how often a company's website is cited and recommended in AI search (Gemini).

Enter a URL and see your Gemini exposure against competitors—an advanced LLMO (AI search optimization) analysis tool in Japan.

Background: AI Search Was Hard to Measure

With generative AI such as ChatGPT and Gemini in wider use, more people ask AI directly and decide based on the companies and services that appear in the answer.

Companies, meanwhile, face challenges like these:

• They do not know whether their brand appears in AI answers.

• They cannot see why competitors keep getting recommended.

• They cannot measure the impact of their work in hard numbers.

Those gaps were common.

LLMO should run as measure → improve → remeasure, but a practical measurement method barely existed.

What Is the LLM Visualization Analysis Tool?

This free tool automatically analyzes and visualizes citation and recommendation status in AI search (Gemini) from a company website URL alone.

How it works

1. Automatically parse the URL and extract semantic structure.

2. Automatically generate likely user questions.

3. Run Gemini Search.

4. Record brand exposure and citation sources.

5. Visualize results as a competitive comparison.

Analysis rests on actual AI answer data, not speculation.

Three Metrics You Can Visualize

① Brand ranking (competitive comparison)

• Display rate (%)

• Citation count

• Average rank

Compare numerically how often your company and competitors appear in AI answers.

② Results by prompt (win/loss by question)

For each question, you can review in detail:

• Which brands appeared

• Which sources were referenced

Those details are available per prompt.

③ Source analysis (identifying citation sources)

• Mention rate

• Average rank

• Number of sources

Work backward from citation sources to see why competitors win.

How This Differs from Older Approaches

Before

• Unclear which questions you lose on

• Competitor strength judged by gut feel

• Programs that only add more articles

After

• Pinpoint issues across questions × competitors × citation sources

• Shift toward a strategy that grows winning patterns

• Build a repeatable improvement loop

Intended Use Cases

• Find why your company is not recommended in AI search

• Analyze competitors' citation structures

• Measure LLMO results quantitatively

• Set priorities for AI search optimization

What's Next

Planned expansions include:

• Support for ChatGPT and Perplexity

• A monitoring dashboard

• Citation-rate correlation analysis

Further feature work is on the roadmap.

Queue is pushing an era where AI search optimization improves through numbers, not intuition.

Service Overview

Tool name: LLM Visualization Analysis Tool
Launch date: January 28, 2026
Price: Free

👉 PR TIMES article
https://prtimes.jp/main/html/rd/p/000000016.000147944.html

👉 Tool page
https://umoren.ai/en/free-tools/llm-visibility