8 Best LLM SEO consultants in 2026: pricing, model, and who they fit

Your buyers ask ChatGPT and Claude for a shortlist before they ever reach your site. They describe their situation, get a few names back, and call those companies. When your brand isn't in that answer, a competitor's is, and you never learn the deal existed. That's usually the moment someone starts looking for an LLM SEO consultant.

Then the search becomes its own problem. Most lists tell you a consultant does GEO or AEO and stop there. What you need to know is who runs your account after you sign, what it costs, and which companies each one is wrong for.

I run a GEO and AEO consultancy, so I sit inside this category. I'm also the first entry below. That's why I built this as a map instead of a ranking. You get eight consultants, what each is built for, who does the work once you sign, and what it costs wherever anyone publishes a number.

One thing to understand before you hire anyone. Getting recommended by a model isn't a separate discipline you bolt onto search. Models pull heavily from the pages that already rank, and they repeat the way other sites describe you. That work belongs inside a search engagement.

What LLM SEO covers, and how GEO and AEO fit

LLM SEO, GEO and AEO are three labels for one job: getting your brand described, cited and recommended inside AI answers. GEO stands for generative engine optimization. AEO stands for answer engine optimization.

You will see consultants use all three terms for identical work.

Some consultants run it inside a search engagement, so the keyword plan, the pages and the outreach all move together.

Others sell it beside one, as a schema audit, reddit engagement, or a prompt dashboard.

The 8 best LLM SEO consultants in 2026 at a glance

Read the "best for" column first. These consultants aren't competing for the same work, and the fastest way through this list is to find the row that matches your situation.

The 8 best LLM SEO consultants in 2026

1. Usama Khan Consulting

Best for: B2B and B2B SaaS companies that want to be visible in LLM answers when their buyers are looking for a solution.

I run Usama Khan Consulting as a boutique SEO and AEO consultancy for B2B and B2B SaaS companies. My roster is capped so I run every account myself. You get me from the sales call onward as your single point of contact, and I bring in specialists I've trained when a piece of work needs them.

The AI search work sits inside the SEO engagement. Your keyword plan and your outreach list both get built around the prompts your buyers use, so one program moves rankings and recommendations at the same time.

The engagement runs on a framework I call VISIBLE:

• Vet the buyer. Study sales calls and onboarding material before opening a keyword tool.
• Identify high-intent keywords. Map 40 to 50 money-making terms before anything gets written.
• Substance over fluff. Every page has to say something original or carry an expert's input.
• Influence the sources. Earn mentions on the third-party pages models already cite for your prompts.
• Benchmark and track. Measure citations and recommendations separately, prompt by prompt.
• Live and fresh. Update published pages as your category moves and the models change.
• Entity clarity. Make every source that mentions you describe you the same way.

Entity clarity is the layer most people skip, and it decides what a model does with everything else.

I start by finding which prompts you're invisible for

Before anything gets written, I run an AI visibility audit on the prompts your buyers use when they're close to a decision. Those prompts go through LLMs like ChatGPT, Claude and Gemini.

The audit answers two separate questions. Are you cited, meaning a model used your page as a source. And are you recommended, meaning the model names you as the answer. Most reporting merges the two into one score, which hides whether anything moved.

It also shows where you're missing, and which competitors come up instead of you for the prompts that matter to your pipeline.

I write from how your buyers describe the problem, not from a keyword tool

Sales calls give me the words buyers use for their own problem. Keyword tools don't contain that language.

Someone describing their situation to ChatGPT talks the way they talk on a call. So content that states what your product does, who it fits and which use case it solves gives a model something concrete to match them against.

I start with bottom-of-funnel keywords first, because they target buyers actively looking for a solution. And they’re also what LLMs reference and recommend based on.

Before a topic goes into production it has to clear two checks. Does it say something original about the subject? And would it hold value that ChatGPT can produce in seconds? A topic that fails both gets a new angle or an expert's input before writing starts.

That's also why I enrich pieces past the text: original data, custom infographics, and insights pulled from expert interviews. Those elements are what make a page worth citing instead of just worth matching.

I get you into the sources models already trust

Visibility across third party pages is now important for how often LLMs recommend you.

My first choice is getting your brand mentioned on pages a model already cites for your prompts. I check which those are and work to get you included. That doesn't always land, and only so many will.

When it doesn't, I work backward. I find the keyword behind the prompt, run SERP analysis on it, then approach the pages ranking for that keyword. I only pitch where your product genuinely belongs, because a mention that describes you wrong does more damage than no mention at all.

You get a dashboard showing whether citations and recommendations are growing across your prompts, month to month.

I also set up conversion tracking against pages and push for a "how did you hear about us" field on your booking form. Analytics won't attribute an AI conversation on its own.

I make every source describe you the same way

Getting mentioned is half the job. What those pages say about you decides whether a model recommends you.

Say your site sells to mid-market operations teams, and a listicle files you under enterprise. A model now has two versions of who you serve. Faced with a buyer describing a mid-market problem, it has weaker grounds for naming you, so it names somebody whose sources agree with each other.

So I audit how you're described everywhere a model can read about you: your own site, G2 and other review platforms, directory profiles, and every listicle you appear in. Where a description is wrong or dated, I go back and get it corrected. Where I pitch new mentions, I supply the positioning myself so the page describes you the way your site does.

Not a fit for: enterprise programs weighted heavily toward top of funnel.

Pricing: strategy engagements from $2,450 a month. Managed engagements from $4,950.

2. Kevin Indig

Best for: companies with an in-house search team that needs strategy and measurement rather than delivery.

Kevin advises fast-growing companies as an independent. He led growth at Shopify and G2 before that, and his site lists clients including Reddit, Ramp, Dropbox and Toast.

What he is built around is published thinking. Growth Memo goes out weekly with his own research on AI search and organic growth, so you can audit how he reasons long before you book a call. Very few people in this category let you do that.

Not a fit for: he advises rather than executes. A team without the capacity to run a plan will end up with a good plan and nobody to deliver it.

Pricing: custom, not published.

3. Dan Petrovic, DEJAN

Best for: Teams that want AI search decisions backed by their own testing rather than by best practice.

Dan runs DEJAN out of Australia, and the practice is built on experiments. He tests how models retrieve and repeat content, publishes what he finds, then builds tooling from it. That includes a custom internal link engine built on language models.

If you want a documented reason behind every change, this is where you get it. If you want somebody to move fast on an established playbook, testing is a slower way to work.

Not a fit for: the client work leans ecommerce and enterprise, and the testing-first approach needs a team with patience for it.

Pricing: custom, not published.

4. Olaf Kopp

Best for: European mid-market and enterprise teams that want research-led GEO grounded in patents and papers.

Olaf co-founded and ran a 40-person agency before going independent. He now consults solo, and he is the only person on this list working directly from patent filings, academic papers and the Google API leak.

He has names for the work: Digital Authority Management, Brand Context Optimization, LLM Readability, and Agentic Commerce Optimization for what happens when agents start doing the buying. He also runs a GEO Research Suite with a patent analyzer and a paper analyzer inside it.

Not a fit for: the practice centres on German-speaking markets and larger companies.

Pricing: custom, not published.

5. Lily Ray, Algorythmic

Best for: publishers and consumer brands whose AI visibility depends on trust and quality signals.

Lily splits her time between Algorythmic, her own solo consultancy, and her role as VP of SEO and AI Search at Amsive. She has spent years documenting how Google judges quality, and she is who the industry quotes on E-E-A-T.

Her work covers content quality audits, algorithm update recovery and Google Discover. If models skip you because they can't tell whether your site is trustworthy, that problem is her ground.

Not a fit for: she takes selective one-to-one work alongside an agency role, and the specialism is publisher and brand shaped rather than pipeline shaped.

Pricing: custom, not published.

6. Marie Haynes

Best for: businesses preparing for agentic search, and sites recovering from Google quality changes.

Marie keeps a deliberately small client list and works further ahead of the curve than most. She wrote a book on the Gemini era of search, and she publishes on the protocols behind agentic browsing, including UCP, MCP and WebMCP.

Her products are diagnostic. An AI Strategy Report tells you where you stand, and a Traffic Drop Assessment tells you what happened. Her retainer is built as coaching for a team, not delivery.

Not a fit for: capacity is limited by her own account of it, and none of the work is done for you.

Pricing: custom, not published.

7. Aleyda Solís, Orainti

Best for: companies selling across several countries and languages.

Aleyda has run Orainti as a boutique consultancy since 2010, with a small number of clients at a time. International and multilingual search is the specialism, which is a genuinely different problem: one page has to earn trust in five markets against five sets of competitors.

She also built LearningSEO.io, which lays out the whole discipline free of charge. Her site names clients including Turo and Trade Republic.

Not a fit for: the engagement is consultancy and audit shaped, built on recommendations, validation and ongoing support rather than a team executing for you.

Pricing: custom, not published.

8. Evan Bailyn, First Page Sage

Best for: healthcare, financial and professional services firms building thought-leadership authority.

Evan founded First Page Sage, and it works as a specialist team of writers, researchers and conversion specialists rather than a single consultant. GEO sits alongside SEO as a named service.

The output is thought leadership: white papers, forecasts and research pieces built to answer what a buyer asks before choosing a firm. In regulated categories, that kind of content is often the only thing that earns a first conversation. Their site names clients including Salesforce, Verizon and US Bank.

Not a fit for: you're hiring a team rather than one senior operator, and the strength sits in regulated and professional services categories.

Pricing: custom, not published.

How to choose an LLM SEO consultant for your situation

These five questions are what separate the right fit from an expensive mistake, and every one of them is answerable on a first call.

Are they optimizing to be cited, or to be recommended?

A citation means a model used your page as a source. A recommendation means it names you as the answer. You can collect citations for months without ever being recommended once.

Ask to see both, separately, for the prompts your buyers use. If the report merges them into a single visibility score, you can't tell which one moved or whether the work is paying off.

Who does the work after you sign?

You know this pattern. A senior person sells the engagement, then the account moves to somebody carrying eight other clients.

Ask who runs the account, how many others that person carries, and whether the person on your call stays on it. The answer tells you what you're buying.

A solo senior consultant sells you their attention and caps the roster to protect it. A specialist team sells you capacity and range instead. Enterprise firms sell both, at a minimum most B2B SaaS companies won't clear.

Is AI search built into the search work, or sold beside it?

Ask what the AI work changes about the pages you publish. Then ask what it changes about the sites you go after for mentions.

Someone running it inside a search engagement can answer both. The visibility audit shows which buying-intent prompts you're missing from, and those gaps go straight into the keyword plan.

The pages then get written to state plainly what you do and who you serve, because that's what a model matches a buyer against. And the outreach list comes from the pages models already cite for those prompts.

Someone selling it beside a search engagement will talk about schema markup and a prompt dashboard. These are nice to have but don’t mean anything without a solid strategy.

What will you see each month, and can any of it reach pipeline?

Attribution here is partial, and anyone telling you otherwise is selling. A buyer gets you recommended in ChatGPT, googles your brand, then books a demo from your homepage. Analytics files that as branded or direct traffic, and most AI-driven visits arrive with no referrer at all.

Ask for three things: prompt-level visibility against named competitors, conversion tracking tied to specific pages, and a "how did you hear about us" field on your booking form. That combination gets you close to the truth. Nothing available today gets you all the way.

What happens when the pages you need mentions on say no?

This is the question I would ask if I were hiring. Getting onto the pages models already cite is the obvious move, and it has a hard ceiling. Plenty of those page owners will ignore you or say no.

Somebody who has done the work will tell you what happens next: find the keyword behind the prompt, run SERP analysis on it, then approach the pages ranking for that keyword instead.

Somebody who has only read about this won't have an answer ready, because the problem only appears once you're actually doing outreach.

Get recommended for the prompts your buyers use

Before you hire anybody, spend an afternoon on this. Write down the five prompts a buyer would type before shortlisting vendors in your category. Run them in ChatGPT and Claude. Note whether you're cited, recommended or missing, and who appears instead of you.

That exercise tells you what kind of help you need, and it's the first thing I do on any new engagement.

Want to see what those prompts return for your category, and what it would take to be in those answers?

Book a call with me and we will go through it together.

FAQs about LLM SEO consultants

What is the difference between LLM SEO, GEO and AEO?

Very little. GEO is generative engine optimization, AEO is answer engine optimization, and LLM SEO names the same territory after the models themselves. Some consultants use one term for content work and another for technical work, but no standard exists. Ask what the work involves rather than what it's called.

How much does an LLM SEO consultant cost?

Almost nobody in this category publishes a price, which is why every entry above says custom. My own strategy engagements start at $2,450 a month, and managed engagements start at $4,950.

Should you hire a consultant or an agency for AI search?

The useful question is who owns your strategy and who executes it. At most AI SEO agencies, a senior person sells the engagement, then the account moves to a strategist carrying eight others. An AEO consultant with a capped roster stays on your account from the sales call onward.

Production volume isn't the dividing line. I run the strategy, the audits and the outreach myself, and I have writers and specialists I've trained to produce at the pace a program needs. So ask who runs your account, how many others they carry, and whether they can produce enough content to move anything.

Hire whoever answers all three without hedging.

How long does it take to show up in AI answers?

Two things set the pace: whether your pages already rank for the terms behind those prompts, and whether your content states plainly what you do and who for. Third-party mentions take longer, because you're waiting on other people to publish. Be careful with anyone promising you a fixed timeline.

Can you attribute pipeline to AI search?

Partly, and the gap is worth being upfront about. Conversion tracking ties demos back to specific pages, and a "how did you hear about us" field catches the conversations analytics misses. Branded search trends give you a rough proxy on top of that. Together they show you the shape of it rather than the full picture.

Author

Usama Khan

Founder, Usama Khan Consulting

Usama runs a boutique, revenue-focused SEO and AI search consultancy for B2B brands. He works with a capped number of clients each month, embedded as a senior fractional strategist. The goal is always the same: make organic a sustainable pipeline channel. When he’s not building search strategies, he’s probably watching cricket or learning more about coffee.

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