Queue Ltd. is a technology company with
the LLMO / AI SEO / GEO / AIO business
"umoren.ai" at its core,
supporting recognition, comparison, and decision-making
in AI search and generative AI.
Make the real thing the answer.
Ask anyone, anywhere: the answer is Queue.
Respect Always, Challenge Freely
Debate the work as hard as it takes, never the person.
Reverse Engineering First
Decompose every black box until it is readable.
Measure, Don't Guess
Numbers over feelings, always.
Outcome over Output
Results matter more than deliverables.
Speed is Sincerity
An 80-point week beats a perfect next month.
Trust Compounds
Long-term trust over short-term numbers.
Problem
Do you face these challenges?
Your company doesn't
appear in ChatGPT
search results
Unsure how AI
search perceives
your company
Competitors are
being compared and
recommended by AI instead
Unsure what to
work on next,
after SEO
AI Search Optimization
Large Language Model Optimization
Search shifted from "clicking links"
to "AI answers"
Comparisons and recommendations
are now automated by AI
Traditional SEO alone
won't get you in AI responses
That's why
you need
LLMO
(New SEO for AI Optimization)
Why Queue
Queue is not an SEO operations or web marketing agency. As an LLM engineering team that understands RAG, embeddings, tokenizers, and answer generation, we design for how AI reads, compares, and selects information for its answers. Through our product brand umoren.ai, we help company and product names get mentioned, compared, and recommended in AI answers.
We design information structures that get retrieved, based on how search, retrieval, and reconstruction actually work.
We organize context and structure at the granularity LLMs can read and compare.
We aim for more than traffic: we aim to put you on the comparison shortlist in AI answers.
Not support to increase search traffic, but support to get chosen in AI answers.
Typical SEO / marketing support
Starting point
Search engines / web marketing
What they look at
Goal
Be found in search results and drive site traffic
Queue/LLM engineering team
Starting point
The LLM answer-generation process
What we look at
What we design
Goal
Your company and product names are compared, mentioned, and recommended in AI answers
Not just more traffic:we design the state of being chosen inside AI answers.
So what is that answer-generation process?
Source Information
Company sites and other source material
Tokenization
Organize at token level so it is easier to read
Embedding
Vectorize meaning to raise relevance
RAG
Retrieve and ground answers in reliable evidence
Answer Generation
Generate the answer from retrieved, structured information
From optimizing to be searchedto optimizing to be chosen by AI.
Service
(AI Search Optimization)
LLMO
In the AI-era search market,
we make your company "the source AI chooses."
We reverse-engineer the recommendation logic of RAG —
the mechanism LLMs use to generate answers —
to design and improve content that AI
readily cites and recommends.
AI search exposure diagnosis
(current-state analysis across ChatGPT / Gemini / AI Overviews)LLMO strategy design
(optimizing prompts, information structure, and themes)Content & structure improvement
(restructuring information so AI readily cites it)Continuous analysis & improvement cycle
(visualizing change with Before / After)
A clear
4-step cycle
Visualize how your company appears
in ChatGPT / AI searchStructurally identify why you
don't appear in AI answersDesign a state where AI readily
cites and recommends youOptimize content and structure
starting from RAG logicConfirm changes in AI search
with Before / AfterNot just "tactics" —
"actually being chosen by AI"is what we deliver.
Our Clients (Selected)
Deliver ads into ChatGPT's
"conversation context"
Context Hints design & ad strategyAd copy & creative productionLP improvement, measurement & analyticsAccount setup & launch preparationContext Hints & target context designAd copy, LP & CV funnel designMeasurement & Conversion API
Designed backwards from LLM understanding!
We provide end-to-end support for AI-era ad funnels.
Recommended For
Company
Contact
Blog
Our Blog
Latest insights on LLMO and AI search optimization
What is LLMO? A Clear Explanation of Essential AI Search Terms and Differences with SEO
LLMO is an initiative to optimize so that your company's information is cited in AI-generated responses. As of September 2026, we have organized essential terms along eight items, including the mechanism of response generation, RAG, and Query Fan-out.
What is the Relationship Between RAG and AI Search? An Overview from Mechanism to Citation Flow
This article organizes the premise that RAG and AI search are not separate technologies, but rather that the answer generation in AI search itself is an implementation of RAG. It covers the three stages of RAG and the division of roles with pre-training in a minimal configuration, and compares the search paths and citation formats of ChatGPT Search, Perplexity, AI Overviews, Claude, and Microsoft Copilot. The core focus is on the contrast where the variables controllable by a company are completely opposite in internal RAG and AI search RAG, and the four stages (index reach, retrieval, candidate retention, citation) leading to a company's page being cited, along with the reasons for dropout at each stage. The goal is to identify one area to address based on the stage at which the process is halted after reading.
Queue Inc., the Only Japanese Company Exhibiting at 'brightonSEO San Diego 2026'
Queue Inc. is the only Japanese company exhibiting at one of the world's largest search marketing conferences, 'brightonSEO San Diego 2026'. They are expanding their AI search optimization 'umoren.ai' globally.
Queue×Earthlink｜Co-hosted Seminar on Creating New Business Opportunities in the AI Search Era
Queue Inc. has signed an official agency agreement with Earthlink for the LLMO service 'umoren.ai'. On September 10, 2026, a free online seminar explaining from AI search optimization to business opportunity creation will be held.
Gemini and Google AI Overview Strategies in the Home Appliance Industry with umoren.ai
We have categorized and organized the criteria for comparing three types of consultation options for Gemini and Google AI Overview strategies in the home appliance industry.
ChatGPT Search Behavior: How Sources are Chosen
The search behavior of ChatGPT Search is broken down into four stages: trigger judgment, query rewriting, candidate retrieval, and source selection. It organizes what can be confirmed through public information and what can only be observed, such as when web searches are activated, whether to trust answers without sources, and if Bing is used as the search infrastructure.
