LLM SEO: How to Make Your Site Visible to AI Assistants

"LLM SEO" is one of several names for the same shift, next to AI SEO, GEO and AEO. Strip the label away and one practical question is left: when someone asks an assistant built on a large language model about your category, can it reach your pages, read them, and find something on them worth repeating?

This guide stays on that practical layer: which crawlers to let in, what stops a model reading a page it was allowed to fetch, how to write pages it can quote, and how to tell whether any of it worked. If you want the bigger picture of why search is changing, AI SEO covers it, and GEO vs SEO vs AEO sorts out the terms.

Reach, read, repeat

It helps to treat LLM SEO as three tests a page has to pass, in order:

1. Reach. The assistant's crawler or fetcher is allowed to request the page, and your server lets it through.
2. Read. The response contains the content as text, not a blank shell waiting for scripts or a picture of a price list.
3. Repeat. The text answers a buyer's question clearly enough that an assistant can quote or paraphrase it, and other sites back it up.

A page that fails the first test never gets to the third, which is why the work starts with crawlers. Every provider fact below comes from that provider's own documentation, checked in November 2026; the rest is our editorial advice, to be tested against your own results.

Reach: know which crawler does which job

The large providers split their bots by job: training, search indexing, and fetches made because a user asked something. That split lets you decline training without disappearing from search answers.

A few details change how you act on that table:

• OpenAI lists four agents in its crawler documentation. The fourth, OAI-AdsBot, is limited to safety checks on landing pages that advertisers submit to ChatGPT. Blocking OAI-SearchBot keeps a site out of ChatGPT's search answers, apart from plain navigational links. Because ChatGPT-User acts on a person's request, OpenAI warns that robots.txt may not govern it, and where GPTBot and OAI-SearchBot are both allowed, OpenAI may reuse a single crawl for search and training.
• Anthropic says on its crawler page that its bots honour robots.txt, and that Claude-User lets site owners control which sites user-initiated requests can reach. Turning Claude-User or Claude-SearchBot off may reduce your visibility in Claude's answers.
• Perplexity says in its crawler guide that PerplexityBot does not gather content for training foundation models, and that Perplexity-User, acting for a user, generally ignores robots.txt. Our Perplexity SEO guide covers the firewall set-up Perplexity recommends.
• Google has no separate AI search crawler. AI Overviews and AI Mode use the normal Search index, and Google's AI features guide says a page needs to be indexed and eligible for a snippet to appear as a supporting link, with no extra technical requirements.

Whether to allow training is a policy choice, and should you block GPTBot? walks through the trade-offs for each vendor. For visibility alone, the rule of thumb is short: let in the search crawler of every assistant your customers rely on. Each of the three vendors in the table publishes IP ranges for its agents, so firewall rules can admit the real crawlers and refuse impostors. To see where your robots.txt stands right now, run the free AI crawler checker.

Read: make sure the fetch returns words

A crawler that is allowed in can still come away with nothing useful. Common causes:

• Content that only appears after JavaScript runs. If the HTML your server sends is an empty frame, a crawler that does not run scripts sees an empty page. Serve the main text in the initial HTML.
• Facts locked in images and downloads. A price table saved as an image, or warranty terms in a PDF brochure, are harder to extract and easy to miss. Put them on the page as text.
• A noindex left over from staging. It keeps pages out of Google's index, and so out of AI Overviews and AI Mode.
• Firewall challenges. A "verify you are human" page is all the crawler receives.

The AI crawler checker also looks for server-rendered text and noindex settings, which covers the first and third. An llms.txt file is sometimes offered as a fix here; the evidence that assistants use it is thin, so treat it as optional and fix the pages first.

Repeat: write pages a model can quote

Once a page can be reached and read, the question is whether it says anything an assistant will want to pass on. These are recommendations to test:

Answer the deciding questions on the page. Buyers ask assistants about cost, comparisons, downsides, reliability and terms. A page per question, or a clear section per question, beats a features page that never mentions price.

Put the answer before the explanation. A heading in the buyer's own words, then a one- or two-sentence answer, then the evidence. That makes the useful sentence easy to find and quote.

Be specific. Numbers, model names, dates and conditions give an assistant something concrete to repeat. "Fast setup" gives it nothing.

Keep every version of a fact in step. When your site, your listings and old announcements disagree, an assistant may repeat whichever it found. Update or retire the stale copies.

Earn mentions elsewhere. Reviews, comparison articles and community threads are sources too, often for the questions your own site cannot answer credibly, such as whether you are reliable.

Consider two invented payroll tools, Acme Payroll and Specimen HR. Acme publishes a pricing page with every tier in a plain table, a page headed "How does Acme Payroll compare with Specimen HR?" and a dated changelog. Specimen HR's pricing sits behind a "contact sales" form and its feature list is a single graphic. The example is about findability, not a forecast of any assistant's output: Acme has left quotable answers in plain sight, and Specimen HR has left very few.

Measure: check what the models say

Pick a fixed set of buyer questions and ask them on a schedule in the assistants your buyers use. For each answer, record separately whether your brand was named and whether your site was cited, because an assistant can do either without the other. Ask the follow-ups too: comparisons, downsides, and which option to buy. Answers vary between askings, so trust trends over weeks rather than any single result, and track two or three rivals on the same questions to separate your progress from changes across the whole category. AI search visibility defines the metrics in more detail.

Measuring it with Vouch

Vouch does the asking for you. Each day it puts your tracked prompts to seven assistants (ChatGPT, Claude, Gemini, Perplexity, Copilot, and Google's AI Overviews and AI Mode). On ChatGPT, Claude, Gemini and Perplexity it also runs Threads three times a week: six-question buying conversations that show the question where a model stops naming your brand and who it names instead. Our methodology page sets out how each assistant is queried and how the answers are scored.

Vouch costs $39 to $599 a month depending on the plan. Access is by invitation while we grow, each invitation opens with a 14-day free trial, and you can ask for one on the waitlist.