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Your buyer asked an AI. It named someone else.
People increasingly get an answer instead of a list of links: they read company names straight out of the AI reply and never reach the search results. GEO Radar asks AI models the same questions your buyer asks — and shows you who gets named instead of you.
What the check actually does
AI visibility is not a metric a model reports. It has to be measured the way a customer would experience it: ask the question, read the answer, count the names. That is exactly what happens here.
- We build the questions a buyer would ask. 16–18 prompts around your category — “who to choose”, “best companies for …”, “X or Y”, and, if you named competitors, direct comparisons.
- We ask several AI models, several times. Each commercial prompt is repeated 3 times: AI answers are not stable, and one run proves nothing.
- We count what came back. Whether you were named at all, in which position, next to whom, and whether the model linked to your site.
- You get a report. A visibility index, the gap map against competitors and the list of answers behind every number.
The report shows what specific models answered at the moment of the check. AI answers drift over time — this is a measurement, not a promise.
Why a Russian-market brand needs a different tool
Western AI visibility trackers watch ChatGPT, Gemini, Claude and Perplexity. That is the right list — for the US and Europe. If your customers are in Russia or the CIS, they are asking Alisa AI inside Yandex and GigaChat inside Sber apps, and those two are invisible to every Western tracker we could find.
GEO Radar asks the models your buyers actually use. See how visibility in Alisa AI, GigaChat and DeepSeek is measured →
The method, in the open
Any number is worthless if you cannot see how it was produced. Ours is deliberately boring and checkable:
- 16–18 prompts. The range is not sloppiness: two extra comparison prompts appear only when you name competitors.
- 3 repeats for every commercial prompt, because a single answer from a generative model is noise, not data.
- Every answer is stored and shown in the report. You can read what the model actually said, not just the score.
- No optimisation is done during the check. The measurement is separate from the work that follows it.
The full methodology, including its limitations, is published in Russian: read the method →
What you can do with the result
A visibility report is not a goal in itself. It usually leads to one of three things:
- Nothing is broken. The models already name you — then the job is to keep it that way and watch the drift.
- You exist, but late. Named fourth or fifth, after competitors. Usually a content and citation problem, and it is fixable.
- You are absent. The models do not know your brand at all. That is the expensive case, and the earlier it is found the cheaper it is to fix.
Work after the measurement — content, citations, presence on the sources models quote — is what our agency does: GEO promotion in AI answers.
Check your brand — free
Fill in five fields. The report opens on this page, usually within 15 minutes, and the link can be saved.
Note on language: the interface is in English, but the detailed report is currently generated in Russian. Ask us in the message and we will send an English summary of your report by email.
Legal documents are published in Russian: the operator is a Russian sole proprietor and the data is processed in Russia under Federal Law 152-FZ.
Frequently asked questions
- What is generative engine optimization (GEO)?
- Generative engine optimization is the practice of making a brand appear, and appear favourably, inside answers generated by AI models — as opposed to ranking a page in a list of links. It starts with measurement: you cannot optimise what you have never measured.
- Which AI models do you check?
- ChatGPT and DeepSeek are running now; Alisa AI (Yandex) and GigaChat (Sber) are part of the product and switch on as their API keys are connected. The report always states which models answered, so a missing model can never be mistaken for a bad result.
- Is it really free?
- Yes. The check costs nothing and needs no account or card. We make money on the work that follows a bad result, not on the measurement itself.
- Why repeat the same prompt several times?
- Because generative models are not deterministic: the same question can produce different company names on two consecutive runs. Repeating each commercial prompt 3 times turns a single anecdote into something you can act on.
- Can you guarantee my brand will be named after the work?
- No, and nobody honestly can. Model answers depend on training data, retrieval and vendor changes nobody outside those companies controls. What can be done is to make the brand present and well described on the sources models actually quote — and to measure the change.
- How is this different from a rank tracker?
- A rank tracker asks where your page sits in a list. Here there is no list: the model returns a sentence with a few company names in it. The unit of measurement is the mention, not the position.