Language models do not browse like people. They retrieve chunks, weigh relevance and reassemble an answer. Content written for that pipeline gets used. Content written purely for a scroll-and-skim reader often does not.
Start a projectWhat you get
Long, meandering pages with the answer in paragraph nine retrieve badly. So do pages where every section repeats the same idea, where claims have no source, and where the brand is described three different ways across the site.
We restructure content into self-contained, clearly labelled sections that survive being pulled out of context, tighten the entity layer, and add schema and sources so a model has something concrete to anchor on.
Sections that stand alone. Each heading states a question or claim and the text beneath answers it fully, without depending on the paragraph above.
Consistent naming, definitions and relationships across pages and schema so a model can build a stable picture of what you do.
Organization, Article, FAQ, Product and Breadcrumb markup applied where it is accurate, giving machines an unambiguous read of the page.
Dates, figures, named authors and links to primary sources. Models favour content that looks like it can be checked.
One intent per page across the topic set. Near-duplicate pages split relevance and make retrieval pick arbitrarily between them.
Scheduled prompt testing plus Search Console data, so changes in how models describe and cite you are recorded rather than guessed at.
We review how your key pages chunk: whether each section is self-contained, whether the answer leads, and where context is lost when text is extracted.
Headings rewritten as questions or claims, answers moved to the top of each section, and repeated filler removed.
Accurate schema, clean internal links and consistent entity references applied across the affected templates.
Prompt testing against the updated pages, repeated monthly, to see whether models now surface the answer we intended.
| Area | Typical approach | Our approach |
|---|---|---|
| Unit of work | Whole page rewrites | Self-contained sections |
| Schema | Applied broadly | Applied only where accurate |
| Volume | More posts | Fewer, better-structured pages |
| Proof | Assertions | Repeatable prompt tests |
Optimising content so large language models can retrieve, understand and reuse it accurately. It focuses on structure, entity clarity, structured data and verifiable evidence, rather than keyword density.
The fundamentals overlap heavily. The extra emphasis is on self-contained sections that make sense when pulled out of the page, and on claims a system can verify against a source.
It helps machines read the page unambiguously and it is required for many search features, so it is worth doing accurately. Treat it as clarity rather than a ranking lever, and never mark up something the page does not contain.
Only if your content is the product and you are protecting it. If you want to be named as a source in AI answers, blocking those crawlers removes you from consideration entirely.
No. In most cases a small number of high-value pages carry the commercial weight. We restructure those first and apply the pattern to new pages going forward.
Through a fixed prompt set tested on a schedule and Search Console trends. It is directional evidence rather than a precise score, and we report it honestly as such.
What is LLM SEO?
Optimising content so large language models can retrieve, understand and reuse it accurately. It focuses on structure, entity clarity, structured data and verifiable evidence, rather than keyword density.
Optimising content so large language models can retrieve, understand and reuse it accurately. It focuses on structure, entity clarity, structured data and verifiable evidence, rather than keyword density.
The fundamentals overlap heavily. The extra emphasis is on self-contained sections that make sense when pulled out of the page, and on claims a system can verify against a source.
It helps machines read the page unambiguously and it is required for many search features, so it is worth doing accurately. Treat it as clarity rather than a ranking lever, and never mark up something the page does not contain.
Only if your content is the product and you are protecting it. If you want to be named as a source in AI answers, blocking those crawlers removes you from consideration entirely.
No. In most cases a small number of high-value pages carry the commercial weight. We restructure those first and apply the pattern to new pages going forward.
Through a fixed prompt set tested on a schedule and Search Console trends. It is directional evidence rather than a precise score, and we report it honestly as such.
Send us the three pages that matter most and we will show you how they read to a retrieval system.