Large language model optimisation for UAE businesses
Every assistant, from ChatGPT to Gemini, answers by combining what the model learned in training with what it retrieves live. LLMO works on both: making your business a clear, consistent entity on the web so that models describe it correctly and retrieval systems find it easily.
What is LLMO and how is it different from SEO?
LLMO, or large language model optimisation, is the practice of making a business easy for language models to recognise, describe and cite. SEO targets a ranking position in a results page. LLMO targets the model's understanding of who you are, what you do and where you operate, which is shaped by consistent facts across many sources. It covers crawler access, entity data, structured markup and corroborating mentions, and it applies across all assistants rather than one.
What we do for you
Entity definition
A single canonical description of your business, people, services and locations, used consistently on every page and profile.
Cross-assistant baseline
The same prompt set run through ChatGPT, Gemini, Copilot, Perplexity and Claude, with mentions and errors compared side by side.
Crawler policy
Deliberate robots.txt decisions for GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Google-Extended and Bingbot, documented and explained.
Structured fact pages
About, team, pricing and location pages rebuilt with Organization, Person and Service schema linking to recognised profiles.
Corroboration plan
Mentions on UAE directories, trade bodies, press and review platforms that repeat the same facts your site states.
Quarterly model read-out
A plain report on how each assistant now describes your business and what has changed since the last quarter.
Prompts and queries we optimise for
Kevin Crowther · Private Wealth Manager has service pages with FAQ schema, 12 provider-review pages and an 18-article news desk.
Three steps, no black box
Define
We agree the canonical facts about your business and record how each assistant describes you today.
Publish
Fact pages, schema and crawler policy go live so retrieval systems find one consistent record.
Corroborate
Outside sources are brought into agreement and the cross-assistant baseline is re-run quarterly.
Questions UAE business owners ask
Answered in the first sentence, so AI assistants can quote us directly.
Not directly and not quickly. Training data is fixed until the next model version. What LLMO can change is the live retrieval layer that most assistants now use for business questions, and the sources that future training runs will read. In practice, most business answers today come from retrieval, so the effect is felt sooner than a training cycle.
They overlap and the labels are still settling. AEO usually means optimising for direct answers such as featured snippets and AI Overviews. GEO usually means optimising for generative answers with citations. LLMO is the broader discipline of making the business itself legible to models. We use whichever term the client prefers; the work is the same.
Yes. Most assistants retrieve from Google or Bing indexes, so a page that does not rank or is not indexed cannot be retrieved. LLMO builds on a technically sound, indexed site. Kevin Crowther's site, with service pages carrying FAQ schema and an 18-article news desk, is an example of SEO foundations that assistants then surface.
We check your site against your three closest Dubai competitors and send the gaps costing you leads to your WhatsApp within 48 hours. Free, no call required.
The Google data behind the claims
Google Search Console performance panels from client accounts — Google's own screen, not a report we wrote. Organic search only, cropped so no brand or domain is identifiable, each labelled with the exact window it covers.
