GEO

Start with the fact most proposals bury halfway down: without an SEO foundation, GEO does nothing. Yandex neural search builds its answer on top of the main results, and Google AI Overviews draws sources mostly from documents already ranking well for the query or its paraphrases. A site that is not indexed, has no trust and does not reach the top twenty will not appear in a generative answer regardless of how much neural optimisation was purchased. Selling GEO as an alternative to SEO is either a misunderstanding of the mechanics or a deliberate simplification.

The engines are built differently and the work only partly overlaps. AI Overviews and Neuro sit on their own search indexes and inherit SEO results directly. ChatGPT and Perplexity use web search plus their own crawlers, so whether you allow those crawlers in robots.txt matters too. GigaChat leans more heavily on large Russian-language sources. What they share is this: what gets quoted is not an optimised page but an extractable passage, meaning a direct answer in the first 40 to 60 words under a heading, concrete numbers, a table, a list of criteria.

On llms.txt it is worth being blunt, because most Russian-language guides get it wrong. It is a community-proposed file at the site root that maps content for language models. It is optional and it is not a standard: Google has said Search does not use it, and no other major engine has confirmed official support. Publishing the file is fine, it costs half an hour and does no harm, but selling llms.txt implementation as the foundation of GEO is not honest. The technical gains come from AI crawler access, correct JSON-LD and a clean heading hierarchy.

Measurement is the weak spot of the entire GEO market. Generative answers are non-deterministic: the same prompt returns different output run to run, so a screenshot of one good answer proves nothing. What you measure is frequency: a fixed list of twenty to forty questions, run weekly against each engine, tracking the share of answers that mention the brand and the share that link to the site. That table produces comparable numbers week over week and turns the effectiveness conversation into a factual one.

Related terms

• SEOSEO is the work on a site and its surroundings that earns organic positions in Yandex and Google: technical foundation, keyword coverage, content, commercial and behavioural signals and links, with the first durable results arriving after three to six months.
• AEOAEO is optimising for direct answers: a page is built so a search engine or voice assistant can extract a ready response to a specific question, whether that is a short paragraph under a heading, a list of steps, a table or a marked-up FAQ block.
• Schema markupSchema markup is structured data based on the Schema.org vocabulary, usually delivered as JSON-LD: it tells search engines and AI answer engines which part of the page is a product, a price, a review, an organisation or a question with its answer.
• LLMAn LLM is a large language model: a neural network trained on vast amounts of text to predict the next token, which is why it can write, summarise and answer, yet it stores no facts the way a database does and can be confidently wrong.
• RAGRAG is a pattern where a language model first retrieves relevant fragments from your own knowledge base and answers from them, which delivers current data and a source citation without any fine-tuning of the model itself.
• Semantic coreA semantic core is an intent-grouped list of the search queries a site should be found for: collected from Wordstat, Webmaster and competitor tools, then clustered by results-page overlap so you know how many pages are needed and what each one covers.

Related services

• GEO: getting your brand cited by AI searchMore and more queries end in an AI answer rather than a click. GEO is the work of getting named in that answer, with a measured mention share rather than a promise.
• SEO and GEO website promotionSearch traffic is the one acquisition channel that keeps working after the ad budget stops. We run two tracks in parallel: classic SEO for Yandex and Google, and GEO, the work of getting your pages quoted inside AI Overviews, Yandex Neuro, ChatGPT and Perplexity, where a growing share of queries now ends. It starts with an audit, never with buying links.
• IT consulting and product auditThe most expensive mistakes in software happen before the first line of code: a misread problem, a stack chosen out of a contractor’s habit, and a specification that does not exist. Consulting exists to settle all of that before the development meter starts running: what to build, out of what, at what cost and in which order. The result is a document, not an opinion on a call.

Read more

• GEO in 2026: how to get cited by ChatGPT, Alice and AI OverviewsGEO is not a separate channel, it is a layer on top of SEO. Here is how six answer engines pick sources, what makes a page quotable, the honest truth about llms.txt, and a weekly method for measuring AI visibility.
• SEO in Yandex in 2026: what changed and what no longer worksLink buying is dead weight, templated copy pushes pages into the low-value bucket, and behaviour manipulation is no longer a grey tactic but a way to lose the site. Here is what actually drives Yandex rankings in 2026.
• Yandex and Google: how promotion differs and how to work with bothOne site, two search engines, two different ranking logics. Where the differences actually change the work, why regional settings matter so much in Yandex, and how to build a strategy without writing everything twice.