Large language models now answer a lot of the questions people used to type into Google. LLM SEO is how you make sure your business is one they know about and trust enough to name.
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LLM SEO is the work of getting your business mentioned and cited by large language models like ChatGPT, Claude, Gemini, and Perplexity. Those tools answer from what they learned in training plus what they find searching the web live, so LLM SEO means being indexed, writing pages with clear, quotable answers, keeping your business facts consistent everywhere, and earning genuine mentions. Tools can track whether you show up, but nobody can guarantee a mention.
LLM SEO is one of several names for the same shift. If you're sorting out the acronyms, start with our SEO vs AEO vs GEO overview.
An LLM, or large language model, is the technology behind ChatGPT, Claude, Gemini, and the answer engine in Perplexity. When a customer asks one of them "who's a good bookkeeper for restaurants in Denver?", it writes a short answer and often names a few businesses. LLM SEO is everything you do to be one of those names, and to be described accurately when you are.
The goal overlaps with generative engine optimization (GEO), but people searching "SEO for LLM" usually want the mechanical version: how these models get their information, which crawlers need access to your site, what llms.txt does and doesn't do, and which LLM SEO tools and services are worth paying for. That's what this page covers.
There are two very different ways a business ends up in an LLM's answer, and they call for different expectations.
In practice, retrieval-based answers tend to favor sources that make the answer easy and safe to repeat: a direct answer near the top of the page, specific facts (services, areas, hours, price ranges), and a business identity that matches across your site, your Google Business Profile, directories, and reviews. Nobody outside these companies can see exactly how they rank sources, and it changes, but that pattern holds up well.
The live-retrieval side only works if the AI company's crawler can fetch your pages. This is the most technical part of SEO for LLMs, and the one most often broken by accident: security plugins, hosting firewalls, and copied robots.txt templates sometimes block AI crawlers without the owner knowing.
Most AI companies now run separate agents for different jobs, so you can allow the ones that fetch pages to answer questions while making your own choice about model training. The main ones, as documented by each company:
| Company | Fetches pages to answer or cite | Collects for model training |
|---|---|---|
| OpenAI (ChatGPT) | OAI-SearchBot, ChatGPT-User | GPTBot |
| Anthropic (Claude) | Claude-SearchBot, Claude-User | ClaudeBot |
| Perplexity | PerplexityBot, Perplexity-User | Not separately listed |
| Google (AI Overviews, Gemini) | Googlebot, the same crawler as Search | Google-Extended (a robots.txt control, not a separate crawler) |
| Microsoft (Copilot) | Bingbot | Controlled through Bing's own settings |
Two practical points. First, blocking Google-Extended does not remove you from AI Overviews, which use regular Googlebot; it only affects how Google uses your content for Gemini. Second, these names and rules change, so check each company's current crawler documentation before editing robots.txt. To test, open yoursite.com/robots.txt and look for any "Disallow: /" line under a user agent you want to allow, or under "User-agent: *".
Once crawlers can get in, the content side is the same as everywhere else: specific, answer-first pages and consistent business facts. Our guides to answer engine optimization and generative engine optimization cover those, and how to rank in ChatGPT has the ChatGPT-specific steps.
The market for LLM SEO tools and LLM visibility tools is young and crowded, and names change fast. Rather than pick winners, here are the categories and what each one is good for.
One caution applies to all of them. AI answers vary by wording, location, account, and plain chance, so a tool's score is a sample of the prompts it ran, not a fixed rank. Use it to watch the trend over months, not to celebrate or panic over one week.
The trade-offs. Costs are described loosely because they vary so much; get real quotes.
| Do it yourself | LLM SEO tool | LLM SEO service or agency | |
|---|---|---|---|
| What you get | You run the checks and make the changes | Automated prompt tracking, dashboards, alerts | Someone else plans the work and makes the changes |
| Cost | Your time, a few hours a month | A monthly subscription; varies widely by prompts tracked | A monthly retainer or project fee; varies widely |
| Fixes anything? | Yes, if you do the work | No, it measures; you still make the changes | Yes, if the scope includes content and listings |
| Best for | One location, a handful of key questions | Many questions, locations, or competitors to watch | Owners with no time and a budget to delegate |
| Watch out for | Letting the monthly check slide | Reading a sample score as a hard ranking | Guaranteed placements and vague reporting |
A tool measures; it doesn't fix. Whatever you choose, someone still has to improve the pages and listings.
llms.txt is a proposed convention: a plain text (Markdown) file you put at yoursite.com/llms.txt that briefly describes your site and lists links to your most useful pages, in a format that's easy for a language model to read. The idea is a bit like a sitemap written for AI instead of for search crawlers.
Here's the status:
So add one if you like, but don't expect it to move anything on its own, and be skeptical of anyone selling llms.txt as the key to AI visibility. Clear pages, structured data, and consistent facts are what the evidence supports.
An illustrative example (not a real customer): a two-person bookkeeping firm in Denver that serves restaurants. The owner writes down eight questions clients ask, like "restaurant bookkeeper in Denver" and "who does payroll for small restaurants in Colorado", and asks each one in ChatGPT, Gemini, and Perplexity, in a fresh chat. That's 24 answers. Say the firm is named in 2 of them, and a local business directory and a competitor's blog are cited again and again.
Over the next two months, the owner rewrites the restaurant page to open with a plain answer ("We handle monthly books, payroll, and sales tax filings for independent restaurants in Denver"), adds a six-question FAQ with schema, fixes an old phone number on two directories, and asks a few happy clients for reviews. Then the same 24 checks again. In this example, the firm shows up in 6.
Those numbers are made up to show the method, not a promise. Real results depend on your market and how the assistants change. The method is the point: fixed questions, a monthly check, and changes aimed at whatever the assistants are citing.
For LLM SEO, Lightsky's SEO assistant, Spica, audits your pages and reads your Search Console data, which shows whether Google has indexed them, the same index many AI tools search. It flags pages that bury their answer and drafts the fixes, and it keeps your business details aligned with your Google Business Profile so models searching the web find one consistent description of you.
It won't buy you placement in a model's answers, because nothing can. Changes wait for your approval, and it's free to start, then pay as you go with credits. See AI SEO for how the assistant handles day-to-day SEO.
Lightsky drafts answer-first pages, adds structured data, and keeps your business details consistent, so search engines and AI tools describe you correctly.
LLM SEO is the practice of making your business easy for large language models, like ChatGPT, Claude, Gemini, and Perplexity, to find, understand, and mention when they answer a question. It's closely related to generative engine optimization (GEO); the names are mostly interchangeable.
Regular SEO aims to rank a page in a list of search results. LLM SEO aims to get your business named inside the answer an AI writes. The two overlap a lot, because LLMs that search the web lean on search indexes, but LLM SEO puts more weight on quotable answers, consistent business facts, and mentions on other sites.
Two ways. First, what the model learned during training, which is fixed at a cutoff date and thin on small local businesses. Second, what it finds when it searches the web in the moment, which most assistants now do for current and local questions. For a small business, the live search side is usually where you can make a difference.
Most fall into three groups: visibility or mention trackers that run a set of prompts through several AI tools and log whether you're named; prompt monitoring that watches specific questions over time and shows which sources get cited; and content or structure checkers that review your pages for clear answers, headings, and structured data.
Not to start. You can check your own visibility by asking ChatGPT, Perplexity, and Gemini your customers' real questions once a month and logging the answers in a spreadsheet. A tool mainly saves time when you track many questions, many locations, or several competitors.
Treat them as samples, not rankings. AI answers vary from one run to the next and by wording, location, and account, so a tool's score reflects the prompts it happened to run. Useful for spotting trends over months; not a precise position like a Google rank.
llms.txt is a proposed convention: a plain text file at the root of your site (yoursite.com/llms.txt) that summarizes your site and points to your most useful pages in a format language models can read easily. It is not an official web standard, and there's no public evidence the major AI search tools rely on it yet.
Not in any proven way today. Search engines don't treat it as a ranking signal, and the major AI assistants haven't said they use it to choose sources. It's cheap to add and harmless, so some businesses add one, but it won't replace clear pages, structured data, and consistent facts.
It can make sense if you don't have time to do the work yourself. Ask what they'll change on your site and listings, how they'll report results, and how they handle the fact that AI answers vary. Walk away from anyone who guarantees a ChatGPT or Gemini placement; nobody can.
That's a business choice, but if you want to show up in AI answers, don't block the crawlers AI assistants use to search the web. Some companies run separate crawlers for search and for model training, which you can often control separately in robots.txt. Check each company's current crawler documentation before you change anything.
Weeks to months, with no set timeline. A new or updated page has to be crawled and indexed before an AI can find it in search, and training data only refreshes when a new model is built. Check monthly and look for the trend.
Lightsky's SEO assistant audits your pages, reads your Search Console data, flags pages that bury their answers, drafts the fixes, and uses the business details you save once in Lightsky, so your name, address, phone, and hours read the same on every page. Everything waits for your approval, and it can't guarantee a mention by ChatGPT, Claude, Gemini, or Perplexity.
Lightsky audits your pages and drafts the fixes for your approval.
Write the answer that gets lifted into snippets, voice, and AI summaries.
The difference between the three, and which to do first.
What earns AI citations, plus a prompt audit you can run today.
What gets a business mentioned in ChatGPT answers, step by step.
Get your pages cited in Google's AI summaries.