LLM SEO
LLM SEO Agency for Getting Cited as the Source
A large language model (LLM) is the model behind every AI engine, and it either learned about you in training or finds you through live search when it answers. We're an LLM SEO agency for funded AI companies that works on both paths, from crawler access to pages written to be cited. HeyOz went from no AI citations to 91.
Led by the former Senior SEO Manager at Invideo AI. Trusted by Viggle AI, HeyOz, Wisemonk and Monk.
Measured against a fixed baseline on every engagement.
- Viggle AI
- HeyOz
- Wisemonk
- Monk
- Zivoke
- TryScent
Two ways an LLM finds you, and where each breaks
Training data is what the model absorbed before release, and you influence it slowly, through what the web says about you. Retrieval is the search the engine runs at answer time, and you influence it through crawler access, indexing and page structure. Retrieval problems are the faster ones to fix, so that's where the work starts.
What our LLM SEO agency fixes, from crawl to citation
We follow the path a retrieval-based answer takes. Can the crawler reach the page, can it read it, does the page hold a quotable answer, and do other sources back it up? Each stage gets checked and fixed in that order.
Covered on every engine your buyers use
- ChatGPT
- Perplexity
- Claude
- Gemini
- Google AI Overviews
- Google AI Mode
- Copilot
- Bing
ChatGPT search and Copilot draw on Bing's index, so Bing rankings feed AI answers. We work on search and AI engines as one program.
How it works
The same four steps on every engagement, with a clear view of what to expect at 30, 60 and 90 days.
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01
Understand
Map your product, buyers, competitors and the prompts and searches that decide your category.
Days 1 to 30. A fixed baseline across every engine and the prompts that matter.
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02
Prioritize
Pick the few moves that will get you recommended fastest and turn them into a focused roadmap.
Days 1 to 30. A focused roadmap agreed, with the first fixes already shipping.
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03
Execute
Do the technical, content, authority and AI visibility work ourselves.
Days 30 to 60. Content, technical and authority work shipping every week.
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04
Improve
Track citations, rankings and conversions against the baseline and keep refining.
Days 60 to 90. A first read against the baseline, then the next quarter planned.
Results we can show you
Every engagement is measured against a fixed baseline set before the work started, so the before and after can be checked rather than taken on trust.
Who this is for, and who it is not for
A good fit
Funded AI companies, seed to Series B, with technical teams and JavaScript-heavy sites
- AI products built as single-page apps
- Developer tools whose docs carry the product facts
- Teams unsure which AI crawlers to allow
- Companies that want to be cited as the source
Not a fit yet
- Teams wanting llms.txt as the whole project
- Sites that must block every AI crawler for legal reasons
- Products with no public pages to index
LLM optimization options for a funded AI company
| SearchAxe | llms.txt generator | Technical SEO agency | Engineering team alone | |
|---|---|---|---|---|
| AI crawler access | Set per crawler, on purpose | Not addressed | Googlebot first, AI crawlers sometimes | Possible, if someone owns it |
| Rendering for crawlers that skip JavaScript | Key pages served as HTML | No | Usually covered | Yes, once it's prioritized |
| Citable page structure | Rewritten passage by passage | No | Rarely in scope | Not their job |
| Outside corroboration | Mentions on sources answers cite | No | Links, not mentions | No |
| Position on llms.txt | Low-cost extra, unproven | Sold as the fix | Varies | Varies |
| Citations measured by engine | Monthly, against a baseline | No | Rarely | No |
What you get each month
- Baseline report Where you stand on every engine and in search before any work starts.
- Monthly AI citation and ranking report Citations by engine, rankings and referring domains, read against the baseline.
- Signups and demos attributed The pipeline that search and AI answers drove that month.
- Slack access A shared channel with the people doing the work.
- Rolling roadmap What shipped, what is next and why, updated every month.
- Competitor movement Which competitors gained or lost ground in AI answers and search, and why.
How we get started
From first call to work in progress in three steps.
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01
Book a free consultation
A call about your product, your market and where you stand in AI answers and search today.
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02
Get a plan and a quote
We send a plan for what we would do first, with a clear quote for the work.
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03
Work starts right away
Once the plan and quote are approved, the work starts immediately.
What clients say
Who's behind SearchAxe
Amit Malvi spent four and a half years at Invideo AI, rising from SEO Executive to Senior SEO Manager. He built and led a 20-person link building team and owned the company's GEO and AEO programs. Today he works hands-on with a small number of AI startups.
Questions buyers ask us
Does llms.txt help us get cited?
There's no evidence it does yet. No major AI engine has said it uses llms.txt to choose what to cite, and Google has said its search doesn't use it. It's cheap to write and harmless, so if you want one we'll add an accurate version. We just won't count it as progress, and we'd never let it stand in for crawler access, readable pages or outside mentions.
Which AI crawlers are for training and which for search?
OpenAI documents GPTBot for training and OAI-SearchBot for search. Anthropic documents ClaudeBot for training and a separate crawler for search. PerplexityBot is documented as the crawler for that engine's search index. Blocking a search crawler can keep you out of that engine's answers, while blocking a training crawler mainly affects what future models learn. We set out the trade-off for each crawler and you decide.
Can you change what a model learned in training?
Not directly, and nobody can. What a model absorbed before release only changes when a newer model is trained. You can shape what the next one sees by making the web describe you consistently across your own pages, review sites, roundups and community threads. Retrieval fixes change live answers much sooner, so we start there.
How long until LLM-based engines cite us?
Retrieval fixes show first. Once a crawler can reach and read a page, engines that search at answer time can cite it after their next visit. Training-data change follows model release cycles, which can mean many months and isn't in anyone's control. We set the baseline in the first 30 days, report monthly, and give the first full read at day 90.
What is LLMO, and is it different from LLM SEO?
Same thing, different label. LLMO stands for LLM optimization, and vendors use it, LLM SEO and a few other names for making a model more likely to retrieve, trust and cite you. The work underneath doesn't change with the name: crawler access, readable pages, citable passages and outside corroboration, measured engine by engine.
Which results came from this kind of work?
HeyOz launched with a single homepage and now has 91 AI citations, from none, and is cited by 6 of 7 major AI answer engines. Viggle AI went from 4 to 279 pages cited in AI answers. Both engagements combined technical, content and authority work, measured against a fixed baseline set before anything shipped.
Why do answers mention us without citing our site?
An answer can name your product from training data, or from a third-party page, without citing any page of yours. That's a mention, not a citation. Mentions show the model knows you. Citations send visits and let you check what was quoted. We track both separately and work on making your own pages the cited source for the prompts closest to a signup.
How do you measure citations each month?
We rerun the same prompts every month on ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews, Google AI Mode and Copilot, and check Google and Bing rankings, since retrieval starts from them. For each prompt we log whether you're cited as a source, mentioned without a link or absent, along with the page or outside source the answer used.
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