Services/AEO/LLM SEO
LLM SEO

LLM SEO Agency: Optimise for the Model, Not the SERP

LLM SEO Agency work targets the layer underneath every assistant: what a language model has read about you, and whether it can retrieve it when asked.

What LLM SEO actually optimises

LLM SEO is the part of answer engine work that sits below any single product. ChatGPT, Perplexity, Gemini and Copilot differ in interface and overlap heavily in what they retrieve, so the useful unit of work is the source material rather than the chatbot.

That means three things in practice: content a retriever can actually parse into discrete claims, an entity record consistent enough that the model does not confuse you with a similarly named company, and sources credible enough to be worth quoting.

It is also the cheapest commercial term in this category to contest. The agency phrasing sits at difficulty 4 and the services phrasing at 3, which is the lowest we have measured anywhere in our keyword set.

Where LLM SEO Wins

hubEntity consistency, so a model resolves your brand to one thing.
fact_checkClaims a retriever can lift without rewriting them.
format_quoteSources credible enough that quoting you is the safe choice.
OUR METHODOLOGY

The LLM SEO Process

01

Retrieval Audit

We check what assistants currently say about you and which sources they draw on, before changing anything.

02

Entity Cleanup

We reconcile your name, category and claims across the places a model is likely to have read them.

03

Claim Structuring

We rewrite key pages so each answers one question in a form a retriever can extract cleanly.

04

Source Building

We earn mentions on sources that already carry standing, because models weight provenance heavily.

05

Prompt Coverage

We map the prompts your buyers actually use and check coverage against them rather than against keywords.

06

Re-measurement

We re-run the same prompt set on a schedule, because a single run of one prompt is a draw and not a measurement.

Frequently Asked Questions

Is LLM SEO different from AEO?
They overlap heavily. AEO is usually framed around a specific surface such as AI Overviews or Perplexity, while LLM SEO is framed around the retrieval layer those surfaces share. We treat the second as the foundation for the first.
Do you optimise for one model or all of them?
All of them, because the work is mostly shared. The differences between assistants are real but smaller than the overlap in what they retrieve, so single-model work is usually poor value.
How do you measure something that changes between runs?
With a fixed prompt set re-run on a schedule and reported as a rate, not a single check. One run of one prompt returns one draw, and presenting that as a measurement is the mistake our own tracker tool refuses to make.
Why is this term so much cheaper to contest than AI SEO?
Because it is newer wording for the same need. Difficulty 4 against 22 for the AI phrasing is a timing advantage rather than a quality difference, and timing advantages close.

Keep exploring

AEO works best layered on solid fundamentals and local intent. Explore how these connect.

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Get retrieved accurately, not approximately.

We will show you what assistants currently say about you and which sources they are drawing on.

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