Independent consultant / UK, Europe & remote projects
LLM SEO Consulting for AI Search Visibility
Make your brand easier to find, verify and represent accurately in search-enabled AI answers.
Work directly with Maksut on an AI visibility baseline, source analysis and the technical or content changes worth implementing first.
Scope, fees and access are agreed before paid work starts. No guaranteed AI citations, recommendations or percentage lifts.
The service
What is an LLM SEO consultant?
An LLM SEO consultant helps a business understand and improve how its website and brand are discovered, retrieved, cited and described in search experiences powered by large language models.
The scope can combine technical SEO, a controlled prompt baseline, source analysis, entity consistency, commercial-page work and measurement. It extends conventional SEO into generated answers.
When the work is useful
- Competitors appear for relevant buying questions while your brand does not.
- AI answers describe your products or services inaccurately.
- Your pages rank, but the answers cite different sources.
- You have AI referrals without a useful measurement framework.
- Your site and third-party profiles present conflicting facts.
Start with the business problem. A new acronym alone is not a reason to commission another audit.
Who this is for
Businesses with a real discovery decision.
SaaS and technical products
Buyers compare tools, capabilities and implementation constraints. The work reviews product facts, source evidence and meaningful competitor questions.
Ecommerce
Product descriptions, availability, feeds and third-party consistency affect what customers can verify. Scope follows the actual catalog and commercial priorities.
Professional services
Customers need to identify a suitable specialist. Service scope, geography, expertise and accurate provider information should support that decision.
WordPress, WooCommerce and expert brands
Where template code, structured data and clear expertise need to work together, I can handle agreed implementation directly.
What I actually do
Research, evidence and implementation.
The proposal defines the pages, customer questions, competitor set, platforms and delivery responsibilities. These are possible workstreams, not a promise that every engagement includes all of them.
AI visibility and competitor analysis
Build a controlled question set around actual customer decisions. Record mentions, recommendations, citations, cited sources, competing providers and factual accuracy with the test conditions.
Branded checks and unbranded discovery stay separate. Repeated observations help distinguish a persistent pattern from one variable answer.
Technical retrieval audit
Investigate indexability, robots rules, canonicals, rendering, internal links, sitemaps, search-facing AI crawlers and infrastructure blocks on the pages that matter.
Search discovery and model training have different controls. Recommendations follow the intended participation policy.
Brand and source consistency
Compare site, profile, product and service facts with relevant external sources. Look for outdated names, incorrect locations, wrong scope or contradictory product information.
Structured data should express real entities and relationships with one clear owner for the base graph.
Content and citation readiness
Improve useful definitions, comparisons, commercial details, evidence and methodology. Choose pages worth updating or consolidating before recommending new content.
The goal is clear, specific information that answers a real task. There is no mandatory “AI chunk” length.
Third-party source footprint
Analyze the publications, documentation, reviews, forums and partner sources that recur in the observed answers. Identify factual corrections and legitimate evidence gaps.
Outreach and external changes require their own agreed scope. I do not create artificial reviews or guarantee placement.
Measurement and follow-up
Compare repeated observations with available first-party reporting, referral visits and qualified enquiries. Document which signals changed and where attribution remains unknown.
For the definitions, see AI search visibility metrics and the AI referral tracking guide.
Not sure where to start?
Run the free AI Visibility Checker for a page-readiness diagnostic. It does not measure live brand visibility across every AI engine; prompt-based research is a separate activity.
A coordinated framework
Seven layers.
One discovery system.
LLM SEO work should explain where a problem sits. A missing citation may require an access fix, stronger evidence or better source information; “publish more” is not a universal answer.
Read how to improve AI search visibility for the implementation decision process.
Eligibility
Can relevant systems access and retrieve the page?
Relevance
Does the page answer the customer’s task?
Evidence
Can the important claims be verified?
Entity clarity
Are the provider, product, service and location unambiguous?
Source corroboration
Does the wider source ecosystem support accurate facts?
Observed visibility
Is the brand mentioned, recommended or cited in the defined sample?
Business impact
Do available visits and enquiries justify the next investment?
What gets audited / what you receive
A report that leads to decisions.
| Area | Review | Possible deliverable |
|---|---|---|
| Visibility | Defined prompts, competitors and sources | Baseline with raw observations and test conditions |
| Technical access | Indexing, crawling, rendering, canonical and internal links | Evidence-backed priority issue map |
| Entities and schema | Brand facts, relationships and duplicate graph ownership | Specific corrections and implementation instructions |
| Content | Intent ownership, commercial information and evidence | Pages to update, merge, create or leave alone |
| External sources | Recurring cited sources and factual consistency | Source analysis and legitimate correction opportunities |
| Measurement | First-party reports, referrals and lead tracking | A repeatable framework and follow-up comparison |
The written scope confirms which artifacts you receive, whether changes are implemented directly and what access is needed. Audit findings and implementation are priced and scheduled explicitly.
Already tracking AI visibility?
I can review the evidence and turn findings into a prioritized implementation queue.
Discuss the findings and scope →Platforms covered
Measure each environment separately.
We choose relevant platforms and available access before the engagement. A defined sample is useful evidence, but it does not represent every user or every answer.
Native reporting, prompt observations and referrals answer different questions. Reports identify the data source and its coverage.
Google AI Search
Review eligibility, the Search generative AI control and available Generative AI performance impressions. The report is not a complete prompt or citation transcript.
Bing and Microsoft Copilot
Use available cited-page, grounding-query and Citation Share reporting. These describe supported Microsoft and partner surfaces, not a universal AI rank.
ChatGPT Search
Record search-enabled answer mentions, recommendations and citations separately from measurable referral visits.
Perplexity
Review source selection, cited pages and competitors in the agreed question sample. The Perplexity SEO guide explains the underlying approach.
Other search-enabled products
Include Gemini, Claude or other systems when they fit the customer journey and offer suitable search or measurement access. Coverage is agreed rather than assumed.
LLM SEO / SEO / GEO / AEO
Overlapping work with a specific scope.
The broader SEO & AI Search service covers the overall organic discovery and conversion system. This engagement focuses on generated-answer visibility, source accuracy and measurement.
AEO, GEO and LLM SEO are useful working terms. They do not create separate official ranking systems. See SEO vs GEO, the AEO guide and what LLM SEO means.
What success actually looks like
- Relevant unbranded questions show the brand more often.
- Important pages earn observed citations.
- Descriptions contain fewer factual errors.
- Coverage improves in the agreed question set.
- Available AI referrals and qualified enquiries improve.
Metrics need denominators and context. A proprietary score moving upward is not sufficient evidence of business value.
Engagement model
Agree, investigate,
implement and compare.
Start with a focused audit, an implementation project or support for your existing team. Share the URL, target customers, markets, competitors and the outcome you want to improve.
Scope, fees, third-party costs, milestones and responsibilities are confirmed in the proposal. There is no universal timeline for indexing, retrieval or citation changes.
Baseline
Agree the customer decisions, priority pages, question set and measurement conditions.
Audit
Review access, entities, content, evidence, sources and commercial information.
Implementation
Build agreed WordPress or WooCommerce changes, collaborate with your developers or provide implementation-ready instructions.
Measurement
Repeat the checks and compare available outcomes with the original sample. Explain the limits before choosing the next task.
Direct specialist support
Work directly with Maksut.
The work crosses technical SEO, content, entity architecture, structured data and web development. A crawler issue may require infrastructure changes; a schema conflict may require a template fix.
I can work on those technical layers directly or coordinate with your existing team. About Maksut →
Looking for an LLM SEO agency?
Some businesses need a larger agency for broad production and distribution. Others need a senior independent consultant for a focused audit and implementation. I work as the latter, with responsibilities agreed around your team.
What I do not promise
No guaranteed ChatGPT recommendations, Google AI inclusion, universal AI ranking or arbitrary percentage lift. Independent platforms control their answers.
I improve conditions within the agreed scope: eligibility, factual clarity, useful evidence, source consistency and measurement.
Sometimes the next step is less content
A useful recommendation may be to fix a service page, consolidate duplicates, correct external information, improve product data or publish one substantial tool or research asset.
Before you hire
LLM SEO consulting FAQ
Scope, platforms, implementation and what the evidence can establish.
What does an LLM SEO consultant do?
Review how a brand and its pages are discovered and represented in search-enabled AI systems, then recommend or implement improvements to access, content, evidence, entities and measurement.
Is LLM SEO different from traditional SEO?
It adds generated-answer mentions, citations, source behavior and accuracy to familiar search and conversion work. Strong conventional SEO remains a foundation.
Can you guarantee ChatGPT recommendations?
No. Third-party systems control their answers. The work improves conditions you can influence and measures a defined sample honestly.
Do I need separate LLM SEO content?
Not always. Improving or consolidating existing commercial and reference pages is often more useful than creating another URL.
Does schema improve LLM SEO?
Correct structured data can clarify supported facts and relationships. It is not a universal citation or ranking guarantee.
Do you work with ChatGPT, Google AI and Perplexity?
Yes, when these fit the agreed customer journey and suitable search or measurement access exists. Each platform is evaluated separately.
Is LLM SEO the same as GEO?
The terms overlap. This service uses them pragmatically within one coordinated discovery and measurement scope.
How long does LLM SEO take?
Delivery milestones are agreed after the starting condition and access are understood. Citation changes have no fixed timeline because recrawling, competing sources and platform behavior are outside the consultant’s control.
Do you provide implementation as well as strategy?
Yes. Agreed WordPress, WooCommerce, structured-data and technical SEO work can be implemented directly, or delivered through briefs and QA for your team.
Which LLM SEO tools should we use?
Choose tools according to the job and evidence needed. The LLM SEO tools comparison distinguishes readiness audits, sampled visibility monitoring and analytics.
Start with the questions that matter
Know what is worth changing first.
Share your website, the customers you want to reach and the gaps you are seeing. We can define a focused audit around current appearances, competing sources, technical eligibility and useful next actions.
The initial conversation defines fit and scope. The paid audit and implementation are agreed separately. The free checker measures page readiness, not live visibility.