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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.

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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.

Our robots.txt blocks the crawlers we need

A security default or a CDN rule can block GPTBot, ClaudeBot or PerplexityBot without anyone deciding to. The engine then can't fetch the page it would have cited.

AI answers still describe our old product

The model learned about you before your last pivot, so answers without search repeat the old pitch. Only retrieval, or a newer model trained on a web that describes you correctly, replaces it.

We were told llms.txt would fix it

Someone added an llms.txt file and waited. No major AI engine has said it uses llms.txt to choose what to cite, so it can't stand in for crawlable pages and outside sources.

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.

01

Crawler access you chose on purpose

We review robots.txt, CDN and firewall rules for GPTBot, OAI-SearchBot, ClaudeBot, Anthropic's search crawler and PerplexityBot, and separate training crawlers from search crawlers so you decide on each.

02

Pages readable without JavaScript

Key product, pricing and docs pages served as HTML text a crawler can read on first fetch, through server rendering or pre-rendering.

03

Passages built to be lifted

Definitions, short answers under question headings, tables and concrete specs, the units a model can quote without rewriting them.

04

Indexed where retrieval starts

Google and Bing indexing confirmed for every page that matters, since ChatGPT search and Copilot draw on Bing's index.

05

Corroboration from outside your site

Mentions on review sites, roundups and communities that repeat your facts, so a model meets the same description from more than one source.

06

llms.txt as a cheap, unproven extra

If you want one, we write an accurate llms.txt. It sits last on the list, is never counted as progress and never replaces anything above.

Covered on every engine your buyers use

  • ChatGPT
  • Perplexity
  • Claude
  • Gemini
  • Google AI Overviews
  • Google AI Mode
  • Copilot

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.

  1. 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.

  2. 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.

  3. 03

    Execute

    Do the technical, content, authority and AI visibility work ourselves.

    Days 30 to 60. Content, technical and authority work shipping every week.

  4. 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.

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.

  1. 01

    Book a free consultation

    A call about your product, your market and where you stand in AI answers and search today.

  2. 02

    Get a plan and a quote

    We send a plan for what we would do first, with a clear quote for the work.

  3. 03

    Work starts right away

    Once the plan and quote are approved, the work starts immediately.

What clients say

We had thousands of pages going nowhere. Amit cleaned that up and rebuilt our landing pages. Our top three rankings are up 362% and our citations across AI engines have grown more than a hundred times.

Nan Ha Nan Ha Product Growth Lead, Viggle AI Read the Viggle AI case study

We came to Amit with a good product and almost no search presence. He gave our team a plan we could actually follow. Referring domains are up 183% and our first page rankings have more than tripled.

George Kurdin George Kurdin Co-Founder, Monk Read the Monk case study

Our content was getting published but not landing anywhere. Amit reworked how we format it for AI engines and our citations across all seven engines are up over 400%. The Reddit community he built now brings us leads weekly.

Aditya Nagpal Aditya Nagpal Founder, Wisemonk Read the Wisemonk case study

We launched with a homepage and nothing else. Amit built the search foundation, the landing pages, the blog, the schema. Our domain rating is up 70% and we went from zero AI citations to being quoted by six of the seven AI engines.

Ahad Shams Ahad Shams Founder, HeyOz Read the HeyOz case study

We had multiple pages fighting each other for the same terms. Amit mapped it all out, consolidated what needed consolidating, and rebuilt our service pages. Organic traffic is up 147% and our top three rankings have more than doubled.

Manjunath Thandu Manjunath Thandu CEO, Zivoke Read the Zivoke case study

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.

Let's get your product recommended.

Funded AI startup, seed to Series B? Tell us where you stand and we'll reply within one business day.

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