When buyers ask an AI tool which provider to choose, your brand should be in the answer, described correctly. We track what large language models say about you, fix the gaps, and build the signals they rely on.
LLM SEO (Large Language Model SEO) is the work of getting your brand mentioned, recommended and described accurately when people ask AI assistants like ChatGPT, Claude, Gemini and Perplexity for advice. Instead of ranking a page in a list of links, the goal is to be part of the answer itself.
It matters because a growing share of research now starts in AI tools, and those tools usually name only a handful of brands. If a model doesn't know your business, confuses it with another, or relies on outdated information, you lose the buyer before they ever reach Google. LLM SEO fixes what these models read about you and how easily they can quote it.
Buyers now ask AI tools the questions they used to type into Google. LLM SEO decides whether you are named in the answer, and whether what is said about you is right.
Audit, content, entity signals and tracking, run as one programme by a team that already does SEO and GEO every day.
Five stages, with a prompt-tracking report at the end of every month.
How AI assistants choose which brands to mention, what you can influence, and how to measure it.
Large language models answer in two main ways. Some answers come from what the model learned during training, a large snapshot of the web, books and other text. Others come from live retrieval, where the tool searches the web in real time and summarises the pages it finds, often with citations. ChatGPT search, Perplexity, Gemini and Google AI Overviews all use retrieval for many questions.
Both routes reward the same thing: clear, consistent and widely corroborated information about your brand. If many trusted sources describe you the same way, and your own pages answer questions directly, models are more likely to mention you and to get the details right.
Traditional SEO focuses on ranking pages in Google's results. GEO (Generative Engine Optimisation) focuses on being cited inside AI-generated answers in general. LLM SEO is the part of that work aimed specifically at how large language models understand and recommend brands: entity data, third-party mentions and content they can quote.
In practice the three overlap heavily. Strong technical SEO helps retrieval-based tools find your pages; good GEO content makes those pages easy to cite; LLM SEO makes sure the model has a consistent, accurate picture of who you are.
An entity is a clearly defined thing, such as a company, person or product, that search engines and AI models can recognise. When your business name, services, locations, founders and key facts differ across your website, Google Business Profile, LinkedIn, directories and press coverage, models may merge you with another company, list outdated services or leave you out entirely.
Fixing this means one consistent set of facts everywhere it appears: a detailed About page, organisation schema, author pages for your experts, and updated profiles on the platforms models draw from.
AI tools tend to lift self-contained passages that answer a question directly. Pages that bury the answer in long introductions, or spread one idea across several paragraphs, are harder to quote. Citation-ready content leads with a direct answer, uses clear headings that match real questions, and includes specific facts, figures, comparisons and definitions.
Original data, expert commentary and honest comparisons are especially valuable, because they give a model something it can't find elsewhere and a reason to attribute it to you.
When an AI tool recommends providers, it relies heavily on what other sources say: industry publications, review platforms, comparison articles, directories and discussion forums. A brand that only describes itself on its own website is easy to overlook.
Building these mentions looks a lot like good digital PR: expert quotes in trade media, complete and reviewed profiles on the directories that matter in your category, and being included in the comparison pages buyers and models both read.
There is no official ranking report for AI answers, so measurement is built around a fixed set of prompts that reflect how your buyers ask questions. Each month those prompts are re-tested across ChatGPT, Claude, Gemini, Perplexity, Copilot and Google AI Overviews, recording whether you appear, where, how accurately, and which sources are cited.
Alongside this, AI referral traffic can be tracked in GA4, since visits from tools like ChatGPT and Perplexity show up as referral sources. Together they show whether your visibility inside AI answers is growing and whether it is sending real visitors.
Start with an audit: a set of 20 to 50 real buyer prompts tested across the main AI tools, compared against your top competitors. It usually reveals a few high-impact fixes, such as outdated information, missing comparison content or thin third-party coverage, that can be tackled in the first month.
From there, LLM SEO runs best as an ongoing programme alongside your SEO, because models and their sources keep changing and competitors are working on the same questions.
Send us your website and we'll test your buyer prompts across ChatGPT, Claude, Gemini and Perplexity, and show you where you stand.
Get a Free AI AuditNo credit card · Results in 24 hours