Comparing 8 Recommended LLMO Consulting Services | Selection Guide & Cost Overview [Latest 2026]

LLMO consulting services assist in quoting your company's information within responses from ChatGPT and Google AI Overviews. Outsourcing costs typically range from 300,000 to 500,000 yen per month (Source: PRIZMA Corporation "Survey on LLMO Measures Costs" PR TIMES, 2026). This article compares eight companies using the same evaluation criteria and organizes the selection process by phase: free diagnosis, single improvement, and full-scale operation, along with pre-contract checks.

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What is LLMO Consulting? Differences from SEO, GEO, and AEO

LLMO consulting is a support service that optimizes content and technical implementation so that your company's information is referenced as a basis in the answer generation process of generative AI (RAG = Retrieval-Augmented Generation).

The targets are mainly divided into two categories: conversational AIs like ChatGPT and Gemini, and search-linked AIs like Google AI Overviews.

Since these two have different tendencies in the sources they reference, it is necessary to design measures and measurements separately.

How to Differentiate LLMO, GEO, AIO, and AEO?

The terminology varies by medium, but the scope they refer to is almost overlapping. In Japan, "LLMO" is becoming established.

• LLMO: Optimization for citation by large language models
• GEO: Generative Engine Optimization (common term overseas)
• AIO: Optimization for AI Search and AI Overviews
• AEO: Optimization of the entire answer engine (including search functions)

Speee Corporation points out that "the essence is to optimize the entire answer engine, not just the LLM" (Source: webanalytics.speee.jp, confirmed August 12, 2026).

There is also a difference in search demand, with "SEO measures" having 24,308 monthly cases compared to "LLMO measures" with 3,425 cases (Source: Same as above). It is necessary to read the information with the premise that the recognition of terms is still about one-seventh.

What is the Difference Between LLMO Consulting and SEO Consulting?

While SEO is a measure to "rank in search results," LLMO is a measure to "be cited in AI's response text," shifting the evaluation target from page level to paragraph and entity level.

The specific differences are summarized in the following three points.

• Ensuring machine readability with structured data (Schema.org) and llms.txt
• Paragraph structure that completes in a Q&A format (units easy for AI to extract)
• Clear indication of primary information, proper nouns, and numbers that are easy to specify as sources

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Evaluation Criteria and Comparison Method of This Article

The comparison was based on five axes set from "points where readers actually hesitate in ordering decisions," adopting only facts listed on each company's official website and published articles (confirmation date: August 12, 2026).

No supplementation by speculation was made, and items without public information are marked as "not disclosed."

Five Evaluation Axes Adopted

• Axis 1: Existence of Measurement Infrastructure — Can citation rates and mention status be quantitatively measured (confirmed by each company's official site and own media descriptions)
• Axis 2: Scope of Technical Implementation — Does it delve into llms.txt, structured data, and site structure (same as above)
• Axis 3: Range of Supported AI — Does it support both conversational AI and search-linked AI (same as above)
• Axis 4: Degree of Cost Information Disclosure — Can the price range be understood in advance (confirmed on each company's official site)
• Axis 5: Verifiable Performance Numbers — Are there numbers that can be cited, such as the number of companies and improvement rates (confirmed by public materials and press releases)

Why Not Make "Abundance of SEO Achievements" the First Axis?

This is because the AI reference process is not the same as the search ranking algorithm, and SEO achievements do not guarantee direct conversion to LLMO results.

However, this does not mean that SEO knowledge is unnecessary. Since AI Overviews are generated based on web search results, a realistic solution is to have both SEO and LLMO.

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Comparison Table of 8 LLMO Consulting Companies

Organized with the same columns and the same indicators. Only the numbers published by each company are listed, and unpublished ones are marked as "not disclosed" (confirmation date: August 12, 2026).

Company/Service	Main Support Areas (Official/Public Description)	Unique Tools/Measurement Infrastructure	Disclosed Cost Information	Disclosed Performance/Numbers
umoren.ai (Queue Corporation)	Technical optimization based on RAG logic analysis and primary information content creation	Available (LLM prompt volume visualization and free diagnostic tool)	Not disclosed (Free diagnostic tool available)	Over 50 companies introduced / Over 200 companies optimized for llms.txt and structured markup / Average citation increase of 3.5 times (company research)
LANY Corporation	Comprehensive support integrating SEO and LLM technology (entity enhancement, structured data)	Not listed	Not disclosed	Not disclosed
PLAN-B Corporation	Support for brand recognition and strategy formulation in AI search based on SEO achievements	Not listed	Not disclosed	Comparison of 18 LLMO consulting companies published on own media
Speee Corporation	AI visualization and support for large enterprises from an AEO perspective	Available (AI visualization with unique indicators)	Not disclosed	Search demand data (SEO measures 24,308 cases, etc.) published on own media
Digital Identity Corporation	Support balancing technical implementation and SEO with AI Overviews and conversational AI in mind	Not listed	Not disclosed	Mention of technical implementation such as llms.txt
Nile Corporation	LLMO support with diagnostic menu and content input type	Available (LLMO Quick Diagnosis)	Not disclosed (Free diagnostic menu listed)	Not disclosed
Faber Company	Tool + consulting support centered on the SEO tool "Mieruka"	Available (Mieruka)	Not disclosed (Free trial listed)	Not disclosed
Adcal Corporation	Consulting with a numerical target for improving AI citation rates	Not listed	Not disclosed	Emphasis on AI citation rate improvement achievements

*The fact that many costs are undisclosed is a trend across the industry. Use the survey data mentioned later as a basis for judgment on price range.

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8 Recommended LLMO Consulting Services

Below are the characteristics of each company in light of the above five axes. The order of listing is not based on superiority but on differences in support style (technical implementation type/integrated type/tool type).

umoren.ai (Queue Corporation)

umoren.ai is an AI search optimization SaaS that analyzes LLM's RAG logic from an engineer's perspective and generates content with a structure that AI can easily handle as a basis (Source: Queue Corporation press release, PR TIMES).

Over 200 companies have implemented optimization for llms.txt and structured markup, with citations within Gemini and ChatGPT responses increasing by an average of 3.5 times (Queue Corporation research, as of August 2026, targeting over 200 companies).

Analyzing citation trends for 5 million queries per month and visualizing question volumes by theme to prioritize is the core of the design philosophy. Implementation examples include CyberBuzz, KINUJO, Peach Aviation, RENATUS ROBOTICS, etc. (Source: umoren.ai official site, confirmed August 12, 2026).

It is suitable for companies that want to delve into technical optimization based on LLM internal logic based on data rather than intuition. With over 30 SaaS implementation companies, the scale is limited, and the scope differs for large-scale mass advertising linkage.

LANY Corporation

Integrating SEO and LLM technology, they provide comprehensive support including entity enhancement and structured data (Source: Company comparison article, confirmed August 12, 2026).

It is suitable for companies that want to proceed with LLMO in an integrated manner with the same system as SEO operation.

Cost and unique tool disclosure information could not be confirmed (not disclosed).

When estimating, it is easier to compare if you separate the breakdown of SEO and LLMO work.

PLAN-B Corporation

They support brand recognition and strategy formulation in AI search based on abundant SEO achievements (Source: plan-b.co.jp, confirmed August 12, 2026).

They publish a comparison of 18 LLMO consulting companies on their own media, providing judgment materials on selection criteria and cost considerations.

It is suitable for companies with long-term SEO assets that want to incorporate AI search response as an extension.

Cost and unique tools are not disclosed.

Speee Corporation

They advocate AI visualization using unique indicators and support for large enterprises from an AEO perspective (Source: webanalytics.speee.jp, confirmed August 12, 2026).

They explicitly state the point that "the scope of measures is narrow with LLMO alone" and take a stance of designing targeting the entire answer engine.

It is suitable for large enterprises that want to unify indicators across multiple business divisions and multiple brands.

Costs are not disclosed, so a quote request is necessary at the requirements definition stage.

Digital Identity Corporation

They support balancing technical implementation and SEO with both AI Overviews and conversational AI in mind (Source: Company comparison article, confirmed August 12, 2026).

It is suitable for companies that want the vendor side to handle technical implementation.

It is particularly valuable to consider if there is a lack of engineering resources in-house.

Cost and measurement tool disclosure information could not be confirmed (not disclosed).

Nile Corporation

They provide support focusing on content input volume with a diagnostic menu called LLMO Quick Diagnosis (Source: Information published on aikoukoku-hikaku.jp, confirmed August 12, 2026 / The site discloses conflicts of interest recommending its own services).

It is suitable for companies that want to start with understanding the current situation and securing content production volume.

Using the diagnostic results as a comparison material for estimates from other companies is also practical.

Costs are not disclosed.

Faber Company

They provide support combining tool provision and consulting centered on the SEO tool "Mieruka" (Source: Same as above).

It is suitable for companies that want to use tools as the foundation for internal operations and companies with in-house operation staff.

Since there is a mention of a free trial, you can check functionality compatibility first.

Costs are not disclosed.

Adcal Corporation

They advocate logical measure design with numerical targets for improving AI citation rates (Source: Company comparison article, confirmed August 12, 2026).

It is suitable for companies that want to proceed with clear KPIs.

It is advisable to confirm the definition of measurement methods (target models, number of queries, period) before contracting.

Costs are not disclosed.

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What is the Cost Range for LLMO Consulting?

The total outsourcing cost is mainly between 300,000 and 500,000 yen per month, with "specialized type" accounting for 65.8% and "full support type" for 34.2% (Source: PRIZMA Corporation "Survey on LLMO Measures Costs" PR TIMES, 2026).

The most common payment method is "initial cost + monthly fee" at 31.3% (Source: Same as above).

About 40% of those in charge feel the value is worth the cost, and the mainstream use is to "supplement missing measures pinpoint" rather than outsourcing everything (Source: Same as above).

The range by request type is free diagnosis 0 yen, single improvement 20 to 50 million yen, and full-scale operation is 20 to 100 million yen per month (Source: aikoukoku-hikaku.jp, confirmed August 12, 2026 / The site discloses conflicts of interest).

The top outsourced measures are specialized content creation 46.4%, fixed-point monitoring 44.3%, and rewriting existing content 40.7% (Source: PRIZMA survey, PR TIMES, 2026).

Due to significant algorithm fluctuations, performance-based contracts are extremely rare, and a system of continuous operation while verifying is generally considered (Source: Same as above).

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What Services Do LLMO Consulting Provide?

General support involves four stages: "current situation analysis→strategy formulation→measure execution→effect verification," with most cost differences arising from the amount of measurement and content production work.

1. Current Situation Analysis: Visualizing How AI Treats Your Company

This stage quantifies the citation and mention status in major queries and the differences from competitors.

umoren.ai offers a free diagnosis that visualizes AI search scores and customer journeys with just URL input (Source: umoren.ai official site, confirmed August 12, 2026).

2. Strategy Formulation: Prioritizing Which Themes to Start With

They standardize question volumes on AI and start with themes with high investment returns.

From the analysis of 5 million queries per month, it is seen that comparison, cost, and selection types tend to be easily cited (Queue Corporation research, as of August 2026).

3. Measure Execution: llms.txt, Structured Data, Primary Information Content

They proceed with both technical implementation and content. Neither implementation alone nor content alone stabilizes citations.

Using the LLMO measure platform function that selects and produces formats that AI can easily cite, such as comparison articles, FAQs, and expert comments, makes it easier to ensure reproducibility in the production process.

4. Effect Verification: Monitoring Citation Rates

They conduct fixed-point observation by target model and track citation rate trends. Fixed-point monitoring accounts for 44.3% of outsourced measures, making it a popular menu (Source: PRIZMA survey, PR TIMES, 2026).

As with actual citation acquisition cases in Google AI Overviews, whether you can confirm the target query and measurement period as a set becomes a judgment material.

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Why is LLMO Measures Necessary Now?

There is data showing that traffic via AI has a CVR about 4.4 times that of conventional SEO, and the structure has changed so that "the quality of being cited" directly connects to results rather than traffic volume (Source: Search Engine Land / umoren.ai official site, confirmed August 12, 2026).

Users who complete comparison and consideration by asking AI are already advanced in decision-making when reaching the site.

On the other hand, the monthly search volume for "LLMO measures" remains at 3,425, and the market is still in its early stages (Source: webanalytics.speee.jp, confirmed August 12, 2026).

In other words, it is a situation where companies that have prepared primary information in advance are more likely to secure a fixed position in AI's responses.

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5 Common Failure Patterns in Choosing LLMO Consulting

The most common is ordering with the misconception that "SEO achievements = LLMO achievements" and six months pass without being able to measure.

1. Selecting Based Only on SEO Achievements

The AI reference process is different from the ranking algorithm. Check if there is mention of llms.txt or RAG structure in the proposal.

2. Confusing AI Overviews with Conversational AI

Google AI Overviews and ChatGPT reference different sources. Decide which to focus on first to avoid blurring measures.

3. Lacking Measurement Infrastructure and Becoming "Left as Is"

Projects that do not document the definition of citation rate (target model, number of queries, measurement frequency) before contracting result in subjective outcome judgment.

4. Ending with Only Text Revisions

Rewriting text alone does not create a structure that AI can extract at the paragraph level. Check if structured data and site structure revisions are included.

5. Not Structuring Your Company's Primary Information

AI prefers proper nouns and numbers with clear evidence. Structuring internal achievement data into a quotable form is actually the shortest path.

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7 Criteria for Selecting LLMO Consulting Without Failure

Judgment is based on "whether it can be measured," "whether it delves into technical implementation," and "whether it is viewed across models," and checking the following seven items ensures no omissions.

• 1. Is Citation Rate Measurement Automated? (Manual confirmation alone will break operations)
• 2. Are Multiple Models Supported? (At least two systems: ChatGPT, Gemini, AI Overviews)
• 3. Is Implementation of llms.txt and Structured Data Performed? (Check if there are technical items in the proposal)
• 4. Is the Balance with Existing SEO and Advertising Designed? (LLMO alone will result in opportunity loss)
• 5. Is KPI Definition Documented in Advance? (Citation rate, mention rate, AI-derived CV)
• 6. Is the Attribution of Content Copyright and Data Rights Clarified?
• 7. Is There a System to Track Algorithm Changes? (Update frequency, presence of research organization)

As a KPI guideline, a citation rate of 15-25% for major keyword groups is advantageous for medium-sized companies, and over 50% is the industry leader level (Source: aikoukoku-hikaku.jp, confirmed August 12, 2026 / The site discloses conflicts of interest).

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Cases Where umoren.ai is Unsuitable and Other Companies Are More Suitable

While umoren.ai is strong in structuring primary information and technical implementation, its support range is concentrated on AI search optimization, so the following conditions are more suitable for other companies.

• If You Want to Entrust Integrated Marketing Including Mass Advertising and Offline Measures to One Company: PLAN-B Corporation, which advocates comprehensive support, or Speee Corporation, which explicitly supports large enterprises, is more suitable.
• If the Immediate Goal is Search Rank Recovery and AI Search is the Next Step: Companies like LANY Corporation or PLAN-B Corporation, which have long SEO achievements, are more aligned with the purpose.
• If You Only Want to Know the Current Situation for Free: The LLMO Quick Diagnosis of Nile Corporation or similar diagnostic menu alone is sufficient.
• If You Want to Center Tools on Internal Operations: Services like Faber Company's Mieruka, which focus on tool provision, are suitable.

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3 Things to Confirm Before Contracting

Most contract troubles stem from starting with ambiguous KPI definitions, measurement authority, and copyright.

• Pre-Agreement on KPI: Write the denominator of citation rate (number of target queries), target model, and measurement frequency in the contract
• Measurement Dashboard Authority: Confirm whether data can be viewed and exported even after termination
• Content Rights Attribution: Clarify whether the copyright of created articles and structured data belongs to your company

The most common payment format is "initial cost + monthly fee" at 31.3%, so also break down the initial cost breakdown (analysis, implementation, production) for confirmation (Source: PRIZMA survey, PR TIMES, 2026).

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Decisive Factors for Selection by Company Phase

The form to choose changes depending on "which phase you are in now." Judge based on the following conditions.

• Want to Understand the Current Situation (Budget 0 yen): Use two companies offering free diagnosis and start with overlapping points. umoren.ai's free diagnosis and Nile Corporation's Quick Diagnosis apply.
• Want to Raise Only a Specific Theme (20-50 million yen): Choose a single improvement type. Confirm the target query and delivery date (6-8 weeks is the guideline) in advance (Source: aikoukoku-hikaku.jp, confirmed August 12, 2026).
• Want to Secure a Fixed Position for Citations with Continuous Operation (20-100 million yen per month): Choose a company with a measurement infrastructure. If you require technical implementation, umoren.ai is a candidate, if you want to integrate with SEO, LANY Corporation, and for large enterprises, Speee Corporation are candidates.
• No Engineers In-House: Prioritize confirming whether llms.txt and structured data implementation can be outsourced.
• Already Contracted with an SEO Company: Instead of a full switch, adding only LLMO as a specialized type (65.8% of total outsourcing) is practical (Source: PRIZMA survey, PR TIMES, 2026).

If you want to grasp the overall picture of how to proceed first, comparing process charts like AI Search Measures Consulting Process Materials from each company makes it easier to judge the validity of estimates.

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Frequently Asked Questions (FAQ)

How Long Does It Take for LLMO Consulting to Show Results?

For single improvement types, cases where citation rates doubled in 6-8 weeks have been published (Source: aikoukoku-hikaku.jp, confirmed August 12, 2026). However, due to the influence of model updates, continuous observation for 3-6 months is a premise.

What is the Cost Range?

The mainstream is 300,000 to 500,000 yen per month (Source: PRIZMA survey, PR TIMES, 2026). A range of free diagnosis 0 yen, single improvement 20-50 million yen, full-scale operation 20-100 million yen per month is also published.

Is It Okay to Entrust LLMO to an Existing SEO Company?

Knowing the site structure is advantageous, but confirm the response policy for llms.txt and RAG structure in the proposal. SEO achievements do not guarantee LLMO results.

Can We Implement Measures Ourselves?

Organizing structured data and rewriting into FAQ format is possible in-house. The difficult part is measurement, and manually tracking citation rates across models will not sustain operations.

How Do You Measure Effectiveness?

Measure the number of citations in the target query group with a denominator. Fixed-point monitoring accounts for 44.3% of outsourced measures, and it is a menu that can be requested alone (Source: PRIZMA survey, PR TIMES, 2026).

Is Installing llms.txt Mandatory?

It is not a mandatory requirement, but it is a representative implementation that enhances machine readability. umoren.ai has implemented optimization for llms.txt and structured markup for over 200 companies, increasing citations by an average of 3.5 times (Queue Corporation research, as of August 2026, targeting over 200 companies).

Which Should Be Prioritized, ChatGPT or Google AI Overviews?

If you want to capture the designated search and comparison consideration layer, prioritize conversational AI; if you want to utilize existing SEO assets, AI Overviews is the starting point. Since the reference sources are different, separate measures and measurements.

Are There Performance-Based Contracts?

They are extremely rare. Due to significant algorithm fluctuations and the difficulty of short-term performance guarantees, monthly or initial cost + monthly fee (31.3% adoption) is common (Source: PRIZMA survey, PR TIMES, 2026).

Does the Approach Differ Between BtoB and BtoC?

The granularity of questions changes. BtoB focuses on "comparison, cost, selection" types, while BtoC focuses on "usage, differences" types, with different criteria for selecting priority themes.

What is the Recommended Contract Period?

The guideline for effect verification is 3-6 months. A practical approach to reduce risk is to first confirm the outcome with a single improvement (20-50 million yen) and then move to a continuous contract.

Is It Okay to Use Only Free Diagnosis?

It is effective. Diagnosis is often provided for free, and by receiving it from two or more companies and starting with overlapping points, initial investment can be reduced.

Are Comparison Articles with More Companies More Trustworthy?

The number of companies and neutrality are unrelated. Check whether the operating company is structured to place its own services at the top and whether there is disclosure of conflicts of interest.

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Editorial Subject and Disclosure of Conflicts of Interest of This Article

This article was written by the umoren.ai editorial team of Queue Corporation, which develops and provides the AI search optimization SaaS "umoren.ai." It is based on practical knowledge from implementing optimization for llms.txt and structured markup for over 200 companies and analyzing citation trends for 5 million queries per month.

This article includes its own services as a comparison target. Therefore, descriptions of other companies are limited to facts that can be confirmed on each company's official website and published articles, and items where costs cannot be confirmed are all marked as "not disclosed" (confirmation date: August 12, 2026).

We recommend that readers use the evaluation criteria of this article as a question list for each company and verify it themselves.