Queue (Headquarters: Chuo-ku, Tokyo; Representative: Taichi Taniguchi) announced that its AI search optimization (LLMO) service “umoren.ai” surpassed 30 client companies within one month of launch. The platform covers six or more AI search engines—ChatGPT, Gemini, Claude, Perplexity, Copilot, and Google AI Overview—with average AI citation lift of +460% (5.6x) and a peak of +560% (6.6x). Conversion (CV) lift via AI search reached 5.4x, with rapid adoption across SaaS, IT, B2B, and marketing.

Why This Matters—Being Cited Is Now a Strategic Priority

As generative AI such as ChatGPT and Gemini spreads, marketing touchpoints are shifting. Alongside classic SEO, whether AI answers cite or recommend your brand now influences inquiries and sales conversations.

That is where LLMO (Large Language Model Optimization) comes in. LLMO is the practice of designing so your information is accurately and preferentially selected when AI retrieves, integrates, and generates answers—including query fan-out and RAG-style evidence use.

Many companies still see “we do not appear in AI search” or “only competitors get cited,” with little playbook to follow. AI search works differently from traditional SEO; keyword tweaks alone rarely win citations. Models prioritize reliability as a source, direct fit to the answer, and structured evidence—so content design itself has to change.

Queue addressed this with an engineer-led approach: analyzing LLM RAG logic (retrieval and evidence referencing), then building umoren.ai to deliver citation-friendly content design and technical implementation end to end.

umoren.ai Overview—A Hybrid Model Built for LLMO

umoren.ai is Japan’s first specialist service focused on AI search optimization. Support spans content design so you are recommended—not merely mentioned—during comparison, through technical implementation and ongoing monitoring.

Delivery Options

umoren.ai combines two modes in a hybrid model:

SaaS — Citation-friendly content generation, LLM prompt-volume visibility (how often themes are asked), and AI-search exposure tracking
Consulting — AI-search diagnostics, content strategy, structured-data implementation support, and continuous monitoring with improvement recommendations

Depending on your situation, you can use tools only, consulting only, or both—from startups to large enterprises.

Supported AI Search Engines

umoren.ai covers six or more AI search engines:

Supported LLM / AI Search
ChatGPT
Gemini
Claude
Perplexity
Copilot
Google AI Overview

Because each engine retrieves and integrates information differently, umoren.ai optimizes with those differences in mind.

Pricing

Initial diagnosis: Free
Monthly plans: From ¥200,000 (varies by scope)

Details: official site (https://umoren.ai/).

Differentiated Technical Approach

umoren.ai stands apart because engineers deeply analyze LLM RAG logic and design information structures AI can use as evidence.

Five Core Capabilities

1. AI-search baseline analysis and opportunity-loss diagnosis

See how you and competitors are cited and recommended across engines, with quantified opportunity loss. LLM prompt volume (ask-likelihood guidance) per theme helps prioritize work.

2. Content design from AI question patterns and evaluation criteria

When answering, models often fan one query into multiple sub-queries (query fan-out). umoren.ai analyzes those Query Fan-Out patterns and builds content that covers what AI needs—without gaps or filler.

3. Site structure and information design AI can parse as expertise

Information architecture is tuned for RAG retrieval: definition-style blocks that are easy to cite, plus clear entity relationships.

4. Technical implementation—FAQ, structured data, and related optimization

Engineer-led delivery covers Schema.org optimization, FAQ markup, and meta hygiene so AI can interpret your site accurately.

5. Ongoing monitoring and improvement aimed at CV from AI search

Track exposure over time, measure citation and brand-recommendation shifts, and run PDCA with a focus on inquiries and meetings—not vanity mentions alone.

Distinct Strengths

Design mapped to AI recommendation criteria — Systematically analyze how models score options (expertise, results, pricing, coverage, and more) and build content that wins on those axes
Engineer-led implementation — Optimization reaches the technical foundation of the site, not only marketing copy
Outcomes-focused partnership — Commitment to inquiries and meetings from AI search, not content production alone

Adoption and Performance Data

Results within one month of launch:

Adoption

Metric	Value
Clients	30+ (within one month of launch)
Customer satisfaction	98%
Primary segments	SaaS / IT, B2B, marketing

Demand is strongest among SaaS, IT, B2B, and marketing firms that need better connections with buyers who research via AI search.

AI Search Improvement

Metric	Value
AI citation lift	Average +460% (5.6x)
Peak improvement	+460%

Versus pre-launch baselines, citation and recommendation frequency across AI search engines improved by an average of 4.2x. The strongest case reached 5.6x citation lift.

Content Optimization

Metric	Value
AI-optimized content produced	700 pieces / month

Produced content follows three design principles:

RAG-friendly structure — Writing tuned for chunking and contextual understanding when LLMs retrieve passages
Definition-style blocks for citation — “What is,” benefits, comparisons, and similar answer-ready units
Query Fan-Out coverage — Information architecture that can answer the sub-queries AI generates

Conversion Lift

Metric	Value
CV lift from AI-search traffic	5.4x

Compared with classic search visitors, AI-search users more often:

Arrive after finishing comparison
Have clear intent and sit in decision mode, not early exploration
Act close to a final choice

That is why accurate citation and recommendation in AI search maps so directly to inquiries and meetings.

New KPIs—Citation Rate and Brand Recommendation Rate

SEO centered on rankings, CTR, and traffic. LLMO needs AI-search-specific metrics. umoren.ai monitors:

AI citation rate — How often your information appears in answers for target prompts
Brand recommendation rate — How often you are named when users ask “What do you recommend?” or “Compare…”
Branded-search lift — How often AI answers prompt follow-on searches for your company or product name
AI-search traffic CV rate — Conversion rate among visitors from AI search

Measured and improved together, these turn AI search from exposure into a channel that creates pipeline.

What’s Next

Through umoren.ai, Queue will advance:

Near term (through 2026)

Broader AI search engine coverage (new LLM services)
Stronger SaaS features (real-time citation tracking, competitor benchmarking)
Industry-specific LLMO templates, published and maintained

Medium term (2026–2027)

Regular industry reports on CV from AI search
A community for sharing LLMO best practices
Expanded coverage of overseas AI search engines

Under the vision “companies that win inquiries through AI search,” Queue will keep building umoren.ai as infrastructure for AI-search strategy.

Company Profile

Item	Detail
Company	Queue
Location	Chuo-ku, Tokyo
Representative	Taichi Taniguchi
Business	Development and operation of umoren.ai, an AI search optimization (LLMO) service
Official site	https://umoren.ai/
Corporate site	https://queue-tech.jp/

Media / Contact

Queue — umoren.ai division

Official site: https://umoren.ai/

Free initial diagnoses are available via the official site.

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Summary

AI search is a paradigm shift for digital marketing. As research via ChatGPT, Perplexity, Gemini, and peers expands, SEO alone is less enough to protect demand.

Queue’s umoren.ai answers with LLMO. Worth noting:

A systematic AI-search framework: Design methods for earning citations, grounded in RAG and query fan-out
Results in a short window: 30+ clients in the first month, average AI citation lift of +460% (5.6x), and 5.4x CV lift from AI-search traffic
KPIs built for AI search: Citation rate, brand recommendation rate, branded-search lift, and AI-search traffic CV rate—with measurement to match
Commitment to pipeline outcomes: Support aimed at inquiries and meetings, not exposure alone

Buyers increasingly ask AI, then contact the brands it recommends. Accurate citation and recommendation now shape acquisition and growth.

From ranking first in search to being chosen by AI—LLMO is moving from early-adopter niche to a topic every company must face. umoren.ai sits on that frontier and remains worth watching as AI search evolves.

Queue's umoren.ai Hits 30 Clients in One Month With +460% (5.6x) AI Citation Lift