umoren.ai Featured on O!Product as an AI Search Visibility Tool

AI and IT services news outlet O!Product has covered Queue's "LLM Visibility Analysis Tool."
The piece introduces it as a free tool that shows how often your brand is cited and recommended in AI search.

O!Product covers Queue's work

O!Product, a news media focused on B2B AI and IT services in Japan, published a story on the "LLM Visibility Analysis Tool" released by Queue.

The article notes that the tool—built as part of the AI search optimization service umoren.ai—lets teams:

• enter a URL

• automatically measure share of voice, citation count, and average rank in Gemini

• compare those metrics against competitors

—all as a free tool.

What the article covers

O!Product highlights these points:

1. Quantifying AI search exposure

What used to be hard to see—"how often does AI cite us?"—can now be tracked with three metrics: share of voice, citation count, and average rank.

2. Competitive brand ranking

You can compare exposure gaps with rivals on the same queries and see where you stand with clear numbers.

3. A measure → improve → remeasure loop

Instead of guessing at content, teams can build a data-backed improvement cycle for LLMO work.

The piece also notes the shift toward a world where AI answers shape decisions.
Against that backdrop, it stresses the value of seeing why a brand is—or isn't—chosen by AI.

About the LLM Visibility Analysis Tool

The LLM Visibility Analysis Tool is an analytics platform designed around how generative AI builds answers.

From an entered URL it auto-generates likely queries, runs Gemini Search,
collects the results, and analyzes them across:

• Brand ranking (share of voice / citation count / average rank)

• Where you appear by prompt

• Domains and sources the AI relied on

That makes it clearer which questions, which competitors, and which sources are driving the gap.

What's next

Building on this release, Queue plans to:

• expand coverage to other AI platforms such as ChatGPT and Perplexity

• strengthen the analytics dashboard

• develop automatic improvement suggestions for LLMO work

These are on the roadmap.

In the AI search era, we'll keep helping teams build the foundation to be chosen and cited.

Read the O!Product article

👉 O!Product article
https://oproduct.ai/articles/3904738