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Lab-OASIS

LLMO extends classical SEO with a new perspective: how your content is seen, evaluated and cited by AI assistants such as ChatGPT, Gemini or Perplexity. The goal is not only higher rankings in Google, but also presence in AI generated answers.
LLMO (Large Language Model Optimization) is a set of principles and techniques that make your content visible and trustworthy for large language models, not only for traditional search engines. While SEO focuses on what Google sees, LLMO focuses on what AI assistants like ChatGPT, Gemini or Perplexity see, understand and decide to use as a source.

Why SEO alone is not enough
Classical SEO is built around organic search results. AI assistants generate answers differently: they combine multiple sources, search for consistent facts and prefer authoritative, well structured and easily quotable content. If you optimise only for traditional SEO, another website can become the preferred AI source even if you have better rankings in the SERP.

What LLMO focuses on
Topics and entities – whether it is clear who and what the page is about.
Answer structure – whether the model can extract short, precise answer units from the page.
Citability – whether there is something concrete to quote and link to.
E E A T signals – experience, expertise, authority and trust.
Structured data – schema.org types such as FAQ, HowTo, Article, Product and others.
The relationship between SEO and LLMO
LLMO does not replace SEO. It builds on it. A fast, technically clean website, correct indexing, internal linking and strong content remain the foundation. LLMO adds another layer – the point of view of the language model. The key question is whether an AI assistant would naturally use your website as a reliable source and mention your brand in its answers.
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