An AI visibility audit measures how often ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews name your brand, how accurately they describe it, and which competitors win the answers you should own. Start with a free snapshot in 48 hours, or commission the full audit — 200+ prompts across five engines and a prioritized 90-day plan — for €3,500.
48-hour snapshot · no sales call · 5 engines
Most teams have a hunch about their AI presence: a prospect mentioned ChatGPT, or someone ran a query once and saw a competitor. A hunch is not a baseline. An AI visibility audit replaces it with numbers: a structured prompt set, run across five engines, scored for how often you appear, how you are described, and who is named instead. It is the same first step we take on every engagement, because you cannot improve a number you have never measured.
The reason this needs its own diagnostic is simple: your existing analytics cannot see it. Google Search Console and rank trackers report on the classic results page. They are silent on whether an AI engine recommends a competitor over you, or which sources it pulls from when a buyer asks for options in your category. Ranking and citation have decoupled. A page can hold position one and never appear in the answer generated above it. The audit measures the scoreboard your other tools do not show, and because it uses the same prompts a real buyer would type, the result is not an abstract score but a transcript of what your prospects are actually being told about you, today, by the systems they increasingly trust to do their research for them.
AI search moved from novelty to default fast. A quarter of Google searches now trigger an AI Overview, roughly half of B2B software buyers consult an AI engine before they ever run a traditional search, and a large share of AI sessions end without a single click to an external site. The buyer reads the answer, forms a shortlist, and moves on. If your brand is not in that answer, you were never in the consideration set, and you have no log of the loss, because nothing showed up in your analytics to record it.
That invisibility compounds. The first brand to be consistently cited in a category becomes the reference others get measured against, and engines reinforce that lead every time they answer. Waiting a few quarters to see how AI search shakes out is not a neutral choice; it is ceding ground that gets more expensive to take back. An audit is cheap insurance against finding out too late. It tells you, with numbers, whether you are building that lead or quietly handing it to a competitor. The brands that act early are not the ones with the biggest budgets; they are the ones who looked first, while the gap was still small enough to close in a quarter rather than a year.
Most visibility tools count mentions and stop there. But being cited incorrectly is its own problem — sometimes a worse one than being absent. When an engine quotes pricing you changed a year ago, lists a feature you retired, or files you under the wrong category, that description reaches buyers as fact. They arrive at demos repeating it, and correcting the record costs you credibility before the conversation even starts.
Our audit checks accuracy as a first-class metric, not an afterthought. We flag where each engine misdescribes you, with the exact prompt and response, so you can see the damage and trace it to its source. It is the difference between "we show up 30% of the time" and "we show up 30% of the time, and a third of those mentions are wrong."
Accuracy problems are also some of the fastest wins an audit surfaces. A wrong price or a stale feature is usually traceable to a specific page, a missing schema field, or a third-party source the model trusts more than yours, all fixable once you can see them. Left unseen, they keep reaching every buyer who asks; corrected, they often improve how confidently the engine cites you at the same time. Most teams are surprised by how much of their AI problem is misinformation rather than simple absence, they were never given a way to detect. Once you can see it, the fix is usually concrete and quick; the hard part was simply knowing it was happening at all, which is exactly what the audit solves.
example finding
"how much does [your product] cost?"
illustrative — your report shows the real prompts and responses
Every audit answers five questions in order, where you stand, who beats you, how you are described, why, and what to do about it.
Your citation rate across ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews, on a prompt set built around how your buyers actually ask — brand, category, comparison, buyer-intent and feature questions. Reported per engine, because an average hides the gaps that matter.
A share-of-answer breakdown showing which competitors the engines name on your priority prompts, how often, and in what position. This is the map of who currently owns your category in AI, frequently a different set of rivals than the ones you track in classic search.
How the engine describes you when it does cite you: right category, current pricing, accurate features. We flag outdated pricing, retired features, wrong-category framing and other confident errors that quietly cost you credibility in buyer conversations, with the exact prompt and response attached so you can verify each one.
The technical and content reasons behind the numbers: crawler access, JavaScript rendering, schema, entity clarity, missing extractable answers and the earned-mention gaps that suppress citation. Each number traces back to a cause you can act on.
A prioritized 90-day action plan that sequences the work by impact — what to ship in the first two weeks, what compounds over the quarter, and what to leave for later. Tied to the four gates of crawl, parse, extract and cite, so the order is never arbitrary.
We show our method because the method is the product. Here is exactly how a brand goes from "we think we're invisible" to a measured baseline and a plan.
We map the questions your buyers ask AI across five intent categories and assemble a representative prompt set, 200+ in the full audit, with your real competitors named.
Each prompt is run across ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews, capturing whether you appear, in what position, and which sources are cited.
We measure citation rate and share of answer against competitors, then validate how each engine describes you, flagging confident errors alongside outright absences.
Findings become a prioritized 90-day plan tied to the gates that block citation: crawl, parse, extract, cite. You leave with a baseline and a sequence, not a screenshot.
How often you are named across the prompt set, per engine. Your headline visibility number, and the one we move first.
Your presence versus each named competitor on the prompts that matter, so you know who you are actually competing with in AI.
The share of your mentions that describe you correctly, category, pricing, features, and where the errors cluster.
The third-party sources each engine cites when answering about your category, the earned-media targets that move citation.
Start free to see whether there is a problem worth solving. Commission the full audit when you want the depth to act on.
free snapshot
€0
delivered in 48 hours
full audit
€3,500
one-time · ~10 business days
The full audit fee credits toward your first month if you move into a Growth or Scale engagement.
None of these require a full GEO program to investigate. They require a baseline, a clear, measured read on where you stand today. The audit is deliberately a low-commitment first step: enough to tell you whether there is a real problem and how big it is, before anyone talks about a retainer. If the numbers come back healthy, that is a useful answer too, and we will tell you so plainly.
We have run this diagnostic enough times to know what tends to surface. The specifics differ, but the shapes are familiar, and recognizing them early is half the value of the audit.
Most brands are cited fine when the prompt already includes them. The gap shows up on category prompts, "best tools for X", where buyers who do not yet know you are the ones forming a shortlist. That is where competitors quietly win.
Presence is rarely even across engines. A brand strong in Perplexity can be absent from AI Overviews because each sources differently. Averaging hides this; the audit breaks it out so you fix the right gap on the right surface.
Pricing from a year ago, a sunset feature, a positioning you have moved past. These confident errors are common and damaging, and they almost never get caught because no one is looking at what the AI actually says.
A CDN rule, a firewall setting, or a robots directive quietly blocks the agents that would index your best content. The technical gate is failing before any content work could matter, and it is usually a fast fix once seen.
Plenty of tools hand you a dashboard and leave you to interpret it. The audit ends with a prioritized plan instead, sequenced against the four gates every page passes through on the way to a citation: crawl, parse, extract, cite. Each finding is tied to the gate it belongs to, so the work has an order and a rationale rather than a backlog of disconnected fixes.
The first two weeks usually target the cheapest, highest-impact gates — unblocking crawlers, fixing rendering, correcting the worst factual errors, shipping schema. The rest of the quarter compounds: rebuilding priority pages for extraction, strengthening entity signals, and beginning the earned mentions that move citation over months rather than days. You finish the audit knowing not just where you stand, but exactly what to ship first, and many teams run the early fixes themselves before deciding whether to bring us in for the rest. We would rather you fix the easy wins yourself and trust us with the hard part than feel locked into a retainer to act on your own data. The audit stands on its own — what you do next is genuinely your call to make.
A single audit tells you where you stand today, and that is the right place to begin. But the engines refresh their knowledge on their own schedule, competitors publish, and your own product changes, so a number that was accurate last quarter drifts. Most B2B teams find a rhythm of a deeper audit two to four times a year, with lighter monitoring in between, keeps the picture current without turning measurement into a full-time job. The first audit sets the baseline; the cadence after it is what turns a one-time look into a trend you can actually steer.
The same clean Q&A format we build into client pages — easy for a person to scan and for an engine to lift.
An AI visibility audit is a diagnostic that measures how often, and how accurately, a brand is named across AI engines such as ChatGPT, Claude, Gemini, Perplexity and Google AI Overviews. It runs a structured set of buyer-style prompts, records where you appear versus competitors, checks whether the AI describes you correctly, and identifies the technical and content gaps blocking citation.
Google Search Console and rank trackers report on the classic results page. They cannot tell you whether ChatGPT recommends a competitor over you, or which sources an AI engine cites when answering a buyer question. Ranking and citation have decoupled, so a brand can rank well and still be absent from AI answers. An AI visibility audit measures the citation scoreboard directly.
The free snapshot is delivered within 48 hours. The full audit takes about 10 business days, because it runs a far larger prompt set across five engines, validates accuracy, and produces a prioritized 90-day action plan.
Accuracy is a core part of it. Most tools only count mentions, but a confident, wrong description, outdated pricing, a feature you retired, the wrong category, reaches buyers as fact and costs deals. We flag where engines misdescribe you, not just where you are missing, alongside competitor share of answer and the source gaps behind both.
No. The free snapshot is a genuine sample, a small set of prompts across the major engines and a short written read on where you stand. There is no sales call required to receive it. If it is useful and you want the full picture, the paid audit goes deeper.
ChatGPT, Claude, Google Gemini, Perplexity and Google AI Overviews. Together they cover the large majority of where B2B buyers ask questions today. Each retrieves and weighs sources differently, so a brand can be strong in one and absent in another, which is exactly why we report them separately rather than as a single averaged score.
Yes. We run audits in English and Spanish with prompts researched natively for each market, not translated. AI search behaves differently across languages and regions, including Google’s "Vista creada con IA" in Spain and "Visión general creada por IA" in Latin America, so a Spanish-market audit uses its own prompt set rather than a converted English one.
The free snapshot takes 48 hours and no sales call. If it shows a gap worth closing, the full audit gives you the depth and the plan to close it.
