How to find an agency that specializes in LLM SEO

TL;DR: There's no dominant "LLM SEO agency" yet. The field is maybe 18 months old. Your best options are boutique GEO consultants, forward-leaning traditional SEO agencies with a dedicated AI practice, and a handful of AI-native shops. This guide tells you exactly what to look for, what to pay, and which questions to ask before signing anything.

What does an LLM SEO agency actually do?

LLM SEO (also called generative engine optimization or GEO) is the practice of making your brand get cited, mentioned, or recommended by AI assistants like ChatGPT, Perplexity, Claude, and Google Gemini. It's different from classic SEO in a few ways that matter a lot.

Traditional SEO is about ranking a URL in a list of blue links. LLM SEO is about being the answer, or at least being named in the answer. The model doesn't send users to ten options. It picks one, two, maybe three brands. If yours isn't among them, you get zero traffic from that query.

A real LLM SEO agency does five things: (1) audits which AI engines currently mention your brand and under which queries, (2) analyzes the content signals and third-party citations that drive those mentions, (3) builds or rewrites content in formats AI models prefer to quote, (4) pursues authority signals like press coverage and structured data that models weigh heavily, and (5) monitors your AI share of voice over time with actual query-level data. If an agency can't describe all five of those concretely, they're just doing regular content marketing and calling it LLM SEO.

For a fuller breakdown of what generative engine optimization actually involves technically, that piece is worth reading before you start agency conversations.

How new is this field and why does that matter for choosing an agency?

The term "generative engine optimization" was coined in a 2023 paper out of Georgia Tech and Princeton [1]. The practice has only existed at any real commercial scale since late 2023, which means the most experienced practitioners in the world have maybe 18 to 24 months of hands-on work behind them. Nobody has a ten-year track record here.

That's not a reason to avoid agencies. It is a reason to be skeptical of anyone claiming proven, repeatable results at scale. The honest shops will tell you the playbook is still being written. A 2024 analysis of citation patterns across ChatGPT, Bing Copilot, and Perplexity found that AI engines cited sources with higher domain authority and stronger backlink profiles at higher rates than lower-authority sites, but the ranking signals differed meaningfully across platforms [2]. There's real signal here. It's platform-specific, and it's not fully mapped.

The implication: an agency that says "we'll guarantee you appear in ChatGPT results" is lying. An agency that says "we'll measure your current AI citation rate, run structured experiments, and improve it over 90 days with documented methodology" is probably telling the truth. Ask which one you're talking to on the first call.

What types of agencies specialize in LLM SEO right now?

The market breaks into four rough categories.

Boutique GEO consultants. Solo practitioners or small teams (2 to 8 people) who came out of technical SEO or content strategy and pivoted hard into AI search. These are often the most technically current because the principals are doing the work themselves. Downside: capacity is limited and they may not scale with you.

Traditional SEO agencies with an AI practice. Mid-size to large SEO shops that added a GEO or AEO service line in 2024. Quality varies enormously. The good ones genuinely rebuilt their methodology; the bad ones just renamed their content services. Ask to see the specific team members running AI work and what they've published or spoken about publicly.

PR and brand agencies pivoting to AI visibility. These can be genuinely good because AI citation is partly a brand authority problem, more than a content problem. If a model doesn't know your brand exists, the fix is often earned media and third-party mentions, which PR people know how to do. The risk is they don't understand the technical content structure side.

AI-native startups with agency arms. A few companies built SaaS tools for AI visibility tracking and added managed services. This can be a strong combo because you get both the tooling and the expertise. The risk is the services side is sometimes understaffed relative to the product side.

For most mid-market B2B brands, the boutique GEO consultant or a traditional agency with a real dedicated practice is the most practical starting point. Enterprise brands probably want a larger shop that can handle program management alongside the strategy.

Estimated monthly retainer ranges by LLM SEO agency type

| | | |---|---| | Boutique GEO consultant | $5,500 | | Traditional SEO agency (AI practice) | $15,000 | | AI-native managed services | $8,750 | | Large agency enterprise program | $50,000 |

Source: Market observation, Spawned research, 2025 (directional estimates; no formal industry survey exists)

How do you vet an LLM SEO agency before signing?

Start with a simple test: ask them to pull a live demo of your brand's current AI citation rate across at least three platforms. Any serious practitioner has tooling to do this. If they can't show you data within 48 hours, that tells you something.

Then ask these questions:

What's your measurement methodology? They should describe specific query sets, how they construct them, and how they track citation rate over time. "We monitor your mentions" is not a methodology.

What's the split between content work and authority/link work? AI citation is driven by both content quality and the authority of the sources that discuss you. An agency that only does one of these will hit a ceiling fast.

Can you show me a before-and-after for an existing client? They don't have to name the client, but they should have anonymized data. If they have no case study-level evidence at all, you're paying to be their first experiment.

Which AI platforms do you optimize for and how do those differ? Perplexity relies heavily on real-time web retrieval, so recency and indexed content matter a lot. ChatGPT's base model uses training data with a knowledge cutoff, though ChatGPT with browsing enabled changes that equation. Claude and Gemini have their own retrieval patterns. A good agency can explain these differences without you prompting them [3].

What do you not do? This question separates thoughtful practitioners from salespeople. Good answers include things like "we don't manufacture fake third-party citations" or "we don't promise specific citation rates because the models are probabilistic." Bad answers are vague positivity.

Also: look at what they've published. Do the founders or lead practitioners have substantive writing on AI search behavior? Have they presented at conferences? Do they have data-backed posts, more than thought leadership fluff? Publication quality is a reasonable proxy for technical depth in a field this new.

What do LLM SEO agencies charge?

Nobody has published a rigorous industry survey on this yet, so treat these ranges as informed estimates based on what's publicly visible in the market.

Boutique GEO consultants: roughly $3,000 to $8,000 per month for ongoing retainers, or $5,000 to $20,000 for project-based audits and strategy engagements.

Traditional SEO agencies with AI practices: $5,000 to $25,000 per month depending on scope, brand size, and the number of platforms covered. Enterprise programs at larger agencies can run $50,000+ per month when they include content production at scale.

AI-native shops with managed services: $2,500 to $15,000 per month, sometimes with a platform fee on top.

One-time audits (understanding your current AI citation baseline) run $2,000 to $10,000 at most reputable shops. If an agency quotes you $500 for a full AI visibility audit, the deliverable will be a template report with your logo on it.

| Agency type | Monthly retainer range | One-time audit range | |---|---|---| | Boutique GEO consultant | $3,000 to $8,000 | $5,000 to $15,000 | | Traditional SEO agency (AI practice) | $5,000 to $25,000 | $3,000 to $10,000 | | AI-native managed services | $2,500 to $15,000 | $2,000 to $8,000 | | Large agency enterprise program | $25,000 to $75,000+ | $10,000 to $30,000 |

Prices are directional estimates; actual quotes will vary by scope, industry, and the specific firm. Always ask for a scoped SOW before committing to a retainer.

What results should you actually expect, and over what timeline?

Honest answer: slower than you want, and harder to attribute than classic SEO.

The fastest measurable wins tend to come from brands that are almost-known by AI models but not quite getting cited. If the models know your category but not your brand, targeted content and earned media can move citation rates in 60 to 90 days. If your brand is genuinely unknown to the model's training data, you're looking at a longer cycle because you need substantive third-party coverage to accumulate first.

The 2023 GEO paper from Georgia Tech and Princeton found that adding authoritative citations and quotation-heavy content to existing pages raised the likelihood of AI citation, though the effect sizes varied by platform [1]. That's the most rigorous published evidence we have right now. It suggests content structure changes can work within a single training cycle, but training cycle timing is not publicly disclosed by most model providers.

For Perplexity specifically, changes can show faster because it retrieves live web content. For ChatGPT's base model, you're partially dependent on retraining schedules. This is why any good agency runs a platform-specific strategy rather than treating all LLMs as interchangeable.

Expect a serious agency to promise measurement and methodology, not specific citation percentages. A 20 to 40 percent improvement in AI citation rate over six months is a reasonable ambition for a brand that's already credible in its category. Starting from zero is a different project.

What are the red flags that an agency is just rebranding old SEO?

This is the most important section if you're talking to multiple agencies right now.

Red flag one: they talk only about content and keywords. Classic SEO keyword optimization does carry over to LLM SEO to a degree, but it's not the primary lever. If an agency's entire pitch is "we'll create content targeting AI search queries," they're doing traditional content marketing.

Red flag two: no measurement infrastructure. Ask: how will you show me my citation rate improving? If the answer is vague ("we'll monitor your brand mentions"), walk away. Legitimate AI visibility tool usage is table stakes for any serious agency.

Red flag three: they confuse AI Overviews with LLM citations. Google's AI Overviews (the summaries at the top of search results) and being cited by ChatGPT or Claude are different systems with partially different optimization strategies. An agency that uses these interchangeably doesn't fully understand the space. Google AI search has its own dynamics worth understanding separately.

Red flag four: guaranteed results. No ethical agency guarantees citation rates. The models are probabilistic, the training schedules aren't public, and the ranking signals shift. Guarantees are a sales tactic, not a service promise.

Red flag five: no discussion of authority signals. AI models cite sources that are cited by other sources. If an agency's strategy has no component for earning press coverage, analyst mentions, or third-party reviews, they're missing a major lever.

Red flag six: a proposal that looks exactly like a traditional SEO proposal with "AI" in the title. If the deliverables are "blog posts, meta descriptions, and technical SEO fixes," that's classic SEO. Fine work, but not LLM SEO.

Should you hire an agency or build in-house LLM SEO capability?

For most companies right now, agency first is the smarter move, and here's why. The field changes fast enough that an in-house hire who learned GEO in 2023 may already be working from an outdated mental model. Agencies that are actively running programs across multiple clients pick up pattern recognition you simply can't get from a single-brand view.

That said, in-house makes sense if you have a content operation that already produces at scale, because the marginal cost of adding AI citation optimization to that existing machine is low. You'd be hiring a strategist to direct existing writers, not building a new function from scratch.

The hybrid model is common for brands that are serious about this: hire an agency for strategy and measurement, use in-house or fractional content teams for production. This keeps costs manageable while getting you external expertise on the strategy side.

One thing worth doing regardless of which path you take: get familiar with the AI search visibility metrics and KPIs that actually matter before you hire anyone. You'll negotiate better contracts and spot weak reporting faster if you know what good measurement looks like.

Which specific agencies or consultants are worth looking at?

I'm going to be honest here rather than give you a name-drop list that may be outdated by the time you read this. The LLM SEO space moves fast enough that a firm that was excellent in early 2024 may have scaled badly by mid-2025, and a new boutique that launched in late 2024 might be the sharpest option now.

What I can give you is a sourcing methodology that won't go stale.

Search for published work, more than agency websites. Find who's writing substantive, data-backed pieces on AI citation mechanics. The researchers at the forefront include academics at Georgia Tech and Princeton [1] [4], plus a handful of independent practitioners who publish on Substack and LinkedIn. Practitioners who can cite studies and explain why they disagree with parts of the research are usually better bets than those who just repeat the consensus.

Look at who's speaking at search and marketing conferences. MozCon, BrightonSEO, and SMX have added GEO tracks. The people presenting actual data from real client programs are worth a conversation.

Ask your network specifically for referrals, not recommendations. A referral means someone hired them and saw results. A recommendation means someone read their content or heard them speak. Both have value but they're different.

Check if they use rigorous tooling. Platforms like those reviewed in our AI SEO tools piece can tell you whether an agency is actually measuring what they claim to measure, or just running ad-hoc spot checks.

If you want a starting-point audit to understand your own baseline before talking to any agency, that's exactly what tools like Spawned are built for. An AI visibility audit gives you independent data so you're not walking into agency conversations blind.

How does LLM SEO differ for B2B versus B2C brands?

The mechanics differ enough that it's worth asking any agency you talk to how they approach this split.

For B2B brands, AI citation often happens during high-intent research queries: "what's the best project management software for engineering teams" or "recommend a CRM for mid-market financial services." The user is evaluating options, and being named here can directly influence a sales cycle. The content that drives these citations tends to be technical, comparison-heavy, and anchored in third-party validation (analyst reports, review sites like G2 or Gartner, press coverage).

For B2C brands, AI citation tends to matter more at the discovery and consideration stage. Someone asking Perplexity for the best running shoes or a weekend travel destination is in an earlier mindset. The content signals that matter are different: consumer review aggregators, editorial coverage in relevant publications, and schema-structured product data.

A B2B-focused agency that's never worked on consumer brands will have real gaps in understanding how AI models handle product discovery queries, and vice versa. Ask for relevant vertical experience, more than LLM SEO experience in the abstract.

Also worth noting: the AI SEO dynamics for local businesses are different again. Local queries in AI assistants are increasingly pulling from maps integrations and review platforms, more than web content. If you're a local or regional business, make sure your agency understands that distinction.

What should your contract and SOW include?

Get these elements in writing before you sign anything.

Baseline measurement before work begins. The agency should document your starting AI citation rate across specified platforms and query sets. Without a baseline, you can't evaluate the program.

Named platforms in scope. ChatGPT, Perplexity, Claude, Gemini, and Bing Copilot have meaningfully different retrieval architectures [3]. Your contract should specify which platforms are included and how each is measured.

Query set definition. What specific queries will they monitor? How were these chosen? You should approve the query set because it defines the success criteria.

Deliverable cadence. Monthly reports minimum. What's in them? Citation rate by platform, content published, authority signals built, and interpretation of what changed and why.

IP ownership. Any content produced for your brand should be owned by you, not the agency.

Exit terms. What happens to your data if you leave? A good agency will give you your historical query-level data. Some won't, and you won't know until you try to leave.

No-guarantee language that's still specific. Ethical agencies won't guarantee citation rates, but they should commit to specific activities and measurement outputs. "We'll conduct a monthly query sweep across 150 branded and category queries and report citation rate changes" is a concrete commitment. "We'll work to improve your AI visibility" is not.

How do AI search visibility tools complement agency work?

Most serious agencies use purpose-built tooling to run query sweeps at scale because doing it manually across thousands of queries across five platforms is not viable. As a client, you benefit from understanding what those tools do and don't measure, because it affects how you interpret the reports you receive.

The core function of an AI search visibility tool is to systematically query AI platforms, parse the responses, and identify whether your brand (and competitors) are cited, how prominently, and in what context. Some tools also track sentiment: more than whether you're mentioned, and whether the mention is favorable, neutral, or negative.

The limitation is that AI model responses are probabilistic. Run the same query twice and you can get a different answer. Good tools account for this by running multiple query variants and averaging results. Bad tools cherry-pick favorable outputs. Ask any agency what their query variance methodology is.

You can also run your own baseline check before hiring anyone, using tools covered in our AI visibility tool overview. Coming into agency conversations with your own data is a real negotiating advantage and a good smell-test for whether the agency's numbers match reality.

For brands tracking their own brandrank.ai visibility insights alongside broader agency work, having an independent data source keeps everyone honest. Agencies performing well won't mind. Agencies performing poorly will hate it, which is useful information.

Sources

1. Aggarwal et al. (Georgia Tech / Princeton), 'GEO: Generative Engine Optimization', arXiv 2023
2. Search Engine Journal reporting on independent 2024 study of AI search citation patterns
3. Perplexity AI, official documentation on how Perplexity works
4. Princeton University Center for Information Technology Policy, AI and Search research
5. OpenAI, ChatGPT model documentation and knowledge cutoff disclosures
6. Anthropic, Claude model documentation
7. Google, AI and search product documentation
8. Gartner, 'Gartner Predicts Search Engine Volume Will Drop 25% by 2026', 2024
9. BrightEdge, 'Generative AI and the Future of Search' research report, 2024
10. Moz, State of SEO report 2024