A1 · Stage 1 — Measure: the baseline everything builds on
Citation Tracker· GEOAI visibility measurement
Being found, included and cited when an AI generates an answer — at answer time, from the live web.
Read the definitionWhen your buyers ask AI for a recommendation in your category, does it name you? We measure exactly that — on each surface separately, with repeated queries.
The Machine equityMachine equity is the business asset that arises from AI systems being able to recognize, understand, recall, recommend — and, on a user's behalf, transact with — a brand. Composed of three layers: rented reach (retrieval visibility), owned memory (trained model recall), and machine buyability (agent-side transactability). Measured honestly only as a portfolio of ranged, per-layer metrics — never as a single blended score.
Read the definition loop
Machine equity is the business asset that arises from AI systems being able to recognize, understand, recall, recommend — and, on a user's behalf, transact with — a brand. Composed of three layers: rented reach (retrieval visibility), owned memory (trained model recall), and machine buyability (agent-side transactability). Measured honestly only as a portfolio of ranged, per-layer metrics — never as a single blended score.
Read the definition- 1 · MEASURE — where you stand and which questions matter (Citation Tracker, Selector)
- 2 · FIX — why the AI skips you, fixed in code (Gap Analysis, Gap Closure)
- 3 · ANCHOR — an unambiguous entity, present where models learn (Entity Anchor, Corpus Campaign)
- 4 · PROVE ↺ — closed-book baseline and the delta at every new model generation (Model Memory Audit, Release Audit)
KG Doctor and the Claim Coherence Engine — the studio's own instruments — serve the entire loop.
AVE Studio doesn't run short-term campaigns: we build our partners' machine equity, across model generations.
Your buyers increasingly ask AI assistants for answers. These surfaces don't list ten links — they typically name just a few brands or providers. The Citation Tracker measures how often you are one of them. We ask real buyer questions on the four AI engines we measure — ChatGPT, Gemini, Perplexity and Google AI Overview — and record who the AI mentions, recommends or cites.
AI doesn't always give the same answer to the same question. So by default we ask every question three times. We report the result not as a deceptively precise number but as a confidence range that shows how stable the measurement is.
Brand name, website address, industry and a short description of your target market, in one questionnaire. Optionally: your own test questions, server access logs or GA4 data.
Quick audit: we examine ten buyer questions across the four AI engines we measure, and give you a visibility score from 0 to 100. A no-obligation picture of where you stand today.
The entry quick check is the only service we offer that returns a single combined score — for orientation. Every paid measurement reports ranges, broken out per dimension.
Buyer questions
We compile the questions that actually come up in your market, based on your client profile, then add your own questions.
Measurement on four AI engines
We ask every question repeatedly on ChatGPT, Gemini, Perplexity and Google AI Overview.
AI-assisted evaluation
The system doesn't just look for your brand name. It recognizes reworded mentions, indirect recommendations and the tone of the answer.
Dashboard and report
Results appear per engine, with trends over time. The online report is shareable, can be password-protected on request, and is available as a PDF.
Every service runs on an application we built in-house for exactly this job — not manual spreadsheets, not general-purpose tools.
Our measurement system: repeated queries across four AI engines, AI-assisted evaluation, confidence ranges — with a dashboard and shareable reports.
- Naming rate per AI engine: we don't blur the results into one generic "AI score".
- Competitor share: shows who the AI names instead of you, and in what order.
- The list of cited sources: shows which websites the AI draws on when it answers about your category.
- The tone of answers about you: shows whether the AI recommends you, merely mentions you, or speaks about you with reservations.
- Real AI traffic arriving on your website: measured from server logs or GA4 data, and kept separate from whether the AI mentions you.
- Change between measurement rounds: shows how your AI presence evolves from one measurement to the next.
Reports are delivered in Hungarian and English.
A separate result for every AI engine
A single merged score would hide which engine has the problem. So we show each engine's result separately.
Repeated measurement, with a confidence range
A one-off query easily returns a random result. We measure repeatedly, and we also show how stable the result is.
Not mere keyword matching
We recognize when the AI refers to you in other words, recommends you indirectly, or cites your content without naming your brand.
A mention and a click are not the same thing
We report separately how often the AI mentions you in the measurement, and how much actual traffic arrives on your website from AI surfaces.
The analysis is expert-led, in pre-defined measurement rounds; it is not automated daily monitoring. Measurement through APIs approximates how the consumer-facing AI surfaces — such as ChatGPT — behave, but is not an exact replica of them. We do not guarantee improved visibility; we deliver verifiable, repeatable measurement. ---
- How much does the baseline visibility audit cost?
- The baseline audit starts from €240 (net). The base price covers the core scope: machine measurement across the major AI surfaces in one language with the core question set, your naming rate with a confidence interval, a 60-minute readout call and the written report. Extra languages or an extended question set are quoted as a fixed add-on after scoping. It is the entry step: every later module builds on this baseline.
- What do I receive?
- A measurement report on whether you appear in the AI answers your buyers actually see: per-question breakdown, naming rate with confidence intervals, a list of competitor mentions, and the readout call. The report is a re-runnable baseline — every later change is measured against it.
- How is this different from a free AI audit?
- Free audits typically judge from a single query — but AI answers vary from run to run. We measure with repeated sampling, confidence intervals and multiple surfaces, so you learn what is stable and what was chance. It is an instrument, not a checklist.
Curious what AI says about you?
Start with the free entry check — no commitment.
Request your free check