Zero-click becomes the norm
Answer engines respond in place. A spot in the link list no longer guarantees attention or a visit.
LLM SEO · AEO · GEO
Optimized for AI answers — not for ten blue links.
geo-rank.ai builds websites that ChatGPT, Claude, Perplexity, Gemini and AI Overviews understand, extract and cite.
We optimize for answers in:
ChatGPT
Claude
Perplexity
Gemini
AI Overviews
Why it matters
Search is becoming a dialogue. The answer arrives without a click.
More and more queries are resolved right inside ChatGPT, Perplexity and AI Overviews — the user gets a ready answer with sources without opening ten tabs. If the model can’t extract and cite your site, you simply aren’t in that answer.
Models read structure, not design
LLMs work with markup, entities and clear statements. A beautiful but machine-opaque page is nearly empty to them.
Classic SEO is no longer enough
Keywords and links don’t control whom the model cites. You need optimization for extraction and citation — AEO / GEO.
What’s included
Seven layers of machine-readability
A full cycle — from clean semantics to entity markup and a multilingual structure that language models understand.
01HTML5
Semantic HTML
Proper header, main, article and heading hierarchy — so structure reads unambiguously.
02JSON-LD
schema.org markup
Organization, Service, FAQPage, Article and more as JSON-LD for precise content understanding.
03/llms.txt
llms.txt
A site map for language models: what you have and what to cite, in a compact text form.
04EXTRACT
Extraction-ready content
Lists, definitions and clear answers — content that’s easy to lift and quote verbatim.
05ENTITY
Entity SEO
We link brand, products and people into an entity graph that models recognize and don’t confuse.
06i18n
Multilingual readability
Correct lang and hreflang, a dedicated URL per language — unambiguous machine-readability.
07AUDIT
Technical audit
Speed, accessibility, rendering, indexing and crawlability — the foundation everything else rests on.
How we work
A transparent five-stage process
From diagnostics to citation monitoring — with clear deliverables at every step.
-
1
Machine-readability audit
We analyze semantics, markup, speed and how models currently see the site.
≈ 1 week -
2
Data architecture
We design content structure, the entity graph and a markup schema for extraction.
≈ 1 week -
3
Implementation
Semantic HTML, JSON-LD, llms.txt, multilingual setup and technical fixes.
2–4 weeks -
4
Citation testing
We test ChatGPT, Claude, Perplexity and Gemini answers on target queries.
≈ 1 week -
5
Monitoring & iteration
We track mentions and citations, and adjust content as models evolve.
ongoing - →
Advantages
Why geo-rank.ai
Engineering, not cosmetics
We work with code, markup and data structure — not stickers on top of a finished site.
This site is the benchmark
The semantics, JSON-LD, llms.txt and multilingual readability we talk about are applied right here.
Seven languages by default
A dedicated page per language (ru, en, de, it, es, fr, zh) with correct lang and hreflang — models know the locale unambiguously.
Measurable results
We track LLM citations and mentions, not just classic ranking positions.
FAQ
Frequently asked
A short take on LLM SEO and how the work is structured.
What is LLM SEO (AEO / GEO)?
LLM SEO means optimizing a site for answer engines: ChatGPT, Claude, Perplexity, Gemini and AI Overviews. The goal is for the model to find, correctly extract and cite your content. AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) are close names for the same approach.
How is it different from classic SEO?
Classic SEO competes for positions in a list of links. LLM SEO works where the user gets a ready answer without clicking: machine-readable structure, entity markup, clear extractable statements and facts the model can reference.
What is llms.txt and why use it?
llms.txt is a text file at the site root that compactly describes the site’s structure and key materials for language models. It helps models quickly understand what exists and what’s worth citing.
How do you measure results?
We track brand citation rate in LLM answers, share of mentions for target queries, traffic from answer engines and the accuracy of extracted facts.
Do you work with existing sites or only new ones?
Both. We start with a technical machine-readability audit, then improve the existing site or design a new one from scratch for extraction and citation.
Do you support multiple languages?
Yes. We implement multilingual machine-readability: correct lang and hreflang attributes, a dedicated page per language, and markup models understand in every language.
How long does a project take?
The technical audit takes about a week. A full implementation cycle usually runs 3 to 6 weeks depending on content volume and number of languages. Exact timing is fixed after the audit.
Get in touch
Start with a machine-readability audit
Leave your contacts and a few words about the project — we’ll reply with an initial assessment and plan.