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AI visibility · audit

What ChatGPT says about your company and who it recommends instead.

I run a fixed set of 40 buying questions through ChatGPT, Perplexity, Google AI Overviews and Copilot, keep the raw answers, and name every company the models put in front of you. You get a report and a prioritised fix list, not a ranking promise.

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From €550 (2 400 zł net)

5.0 out of 5 · 3 reviews

sample · August 2026

AI visibility report

  • ChatGPT, search enabled10 questions, each run 3 times1/10
  • Perplexitycites two industry directories, your listing is in neither2/10
  • Google AI Overviewsan answer appeared on 7 of the 10 questions0/10
  • Microsoft Copilotsources: LinkedIn and one roundup from 20240/10
  • Named instead of you6 companies by name, 4 of them from the same roundups6 firms

Brand mentions across 40 answers3/40

A sample run, not a client. Your numbers will differ, and the measurement changes nothing on its own: the fix list under it does.

Where you start

You do not know whether you exist in AI answers

Four things I see in almost every business before anything is measured.

  • Traffic falls, rankings hold

    Where an AI Overview appears, click-through drops by roughly 34.5% (Ahrefs, 300,000 keywords), and overviews now show on around 92% of informational queries. Position three stays position three, it just stops earning clicks. Analytics shows the dip without the reason.

  • One prompt is not a measurement

    You type your category into ChatGPT once, see a competitor, and draw a conclusion. The same prompt an hour later returns a different list. Without repeats and saved answers you have an impression, not a baseline you can compare against next quarter.

  • Half your site is blank to AI crawlers

    No AI crawler executes JavaScript. GPTBot, OAI-SearchBot, ClaudeBot and PerplexityBot fetch the HTML and stop there, as of June 2026. Prices behind a tab, FAQs in an accordion and reviews loaded after hydration simply do not exist for them.

  • All the effort goes into your own blog

    In a study of 278 B2B SaaS buying prompts (July 2026), 66% of the times ChatGPT recommended a brand it cited that brand's own website nowhere in the answer. The recommendation came out of other people's roundups, mentions and threads. On-site work alone cannot buy it.

What you get

A report that splits straight into tasks

One file plus an appendix with the raw answers from all four engines.

A fixed set of 40 questions

We build 40 prompts your buyer actually types: the category, the city, alternatives to a named competitor, "who can build me X". The set is frozen so the next run is comparable to this one.

Raw answers in the appendix

Every answer from all four engines is saved with its date and the model version used. You do not have to take my word for anything, you can read what the model wrote.

The named list of who wins instead

I list every company that surfaces in answers to your questions and show what put it there: a roundup, a directory, a forum thread, a trade-press mention.

A server-side rendering verdict

I check what survives of your pages in plain HTML with JavaScript off, and how bots are treated in robots.txt and at the firewall. Prices, FAQs and reviews that are invisible get listed separately, URL by URL.

The off-site gap list

Best-of roundups, directories (Clutch, GoodFirms, DesignRush, vertical listings), review platforms, Reddit threads, and whether your company name, description and registration details match across every profile.

A prioritised fix list

Each item carries an effort estimate, who should do it, and whether it sits on your site or off it. A separate block lists what I recommend against, with the reason.

How it runs

Ten working days, four stages

Start on a Monday, report and call two weeks later.

  1. Day 1-2

    The prompt set

    You send 10-15 phrases buyers use to find you and a list of competitors. I turn that into 40 questions and send them for sign-off. Nothing runs before you approve the set.

  2. Day 3-5

    The run across four engines

    Every question goes three times into ChatGPT, Perplexity, Google AI Overviews and Copilot, from a clean session each time. Answers are stored in full, together with the sources each engine listed.

  3. Day 6-7

    The technical pass

    I check what is left of your pages without JavaScript, how bot access looks in robots.txt and at the firewall, and whether your company details agree across the site, your profiles and the directories.

  4. Day 8-9

    The off-site pass

    I find the roundups, directories and threads where competitors are named and you are not. For each one I write down who decides on inclusion and what they ask for.

  5. Day 10

    Report and call

    You get the file, the appendix of raw answers and 60 minutes on a call. You leave with a task list you can hand to anyone, not only to me.

Packages

Audit

from€550

One measurement and the report. You or your team apply the fixes.

  • 40 questions, 4 engines, 3 runs each
  • Raw answers in the appendix
  • The named list of who wins instead
  • Rendering and bot-access verdict
  • The off-site gap list
  • 60 minutes on a call afterwards

Typical fit: a B2B service company, one site, one market.

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Audit with the fixes applied

from€950

Everything above, and I do the technical work on your site myself.

  • Everything in the Audit package
  • Prices and FAQs moved into server-rendered HTML
  • robots.txt and bot access cleaned up
  • Structured data for ranked list pages
  • One company name and details across all profiles
  • A second measurement after the work lands

Next.js, WordPress, Shopify. A bespoke CMS is quoted separately.

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Monthly re-run

from€210/mo

The same question set every month and a report against the last one.

  • The same frozen set of 40 questions
  • Month-on-month difference report
  • New companies that entered the answers
  • Shifts in the sources each engine cites
  • A short task list for the coming month
  • Monthly terms, cancel whenever you want

Worth doing after an audit, not instead of one.

Book the audit

I do not sell positions or guaranteed citations, because nobody controls them. I sell the measurement and the fix list.

When this is the wrong purchase

Four cases where I talk you out of it instead of selling.

  • You want a guarantee that ChatGPT will recommend you. Nobody sells that honestly, and neither do I.
  • You need a result this month. Most of the work sits off your own site and runs on other people's editorial schedules.
  • You want llms.txt written and ticked off. I will not sell it: Ahrefs checked 137,000 sites and 97% of llms.txt files got zero traffic in May 2026.
  • You have no service page with a price and a scope on it. There is nothing to measure yet, the site comes first.

If the real problem is the site itself rather than your visibility in AI answers, start here: Services

No call needed

Fixed estimate in 24 hours

Describe the task in two sentences. You get a fixed price, a timeline and a plan. If it isn't a fit for us, we say so straight away and point you elsewhere.

  1. 01We read the task and ask two or three questions if anything is unclear
  2. 02We put together the estimate: scope, price, launch date
  3. 03It lands in your inbox within a day. The next move is yours

No newsletters, no unsolicited calls. The answer comes by email.

How we handle your data is explained in our privacy policy.

Questions about AI visibility

  • No, and nobody can. Models assemble answers from sources neither you nor I control, and the answer shifts between runs and between model versions. What I sell is the measurement, the named list of who gets recommended instead, and an ordered fix list. The effect is checked by re-running the same question set later.

  • Because a single answer means nothing. The same prompt asked three times can return three different lists of companies, so what counts is how often you appear across repeats, not whether you appeared once. That is why the report gives you a fraction like 3/40 rather than the word "visible".

  • Because that is where recommendations are made. In a study of 278 B2B SaaS buying prompts (July 2026), 66% of ChatGPT's brand recommendations carried no citation of the brand's own site, and the strongest correlate of being recommended was appearing in third-party roundups, followed by branded web mentions and a Reddit presence. On-site work removes technical blockers, but it does not buy the recommendation.

  • No. Ahrefs looked at 137,000 sites and found that 97% of llms.txt files received zero traffic in May 2026, and Google has said plainly that it does not support the format and has no plans to. No major model provider has committed to it either. If you already have the file, leave it, but it does not count as visibility work.

  • Yes, and the problem is a specific one. AI crawlers fetch the HTML and do not execute JavaScript, so prices, FAQs and reviews painted in the browser do not exist for them. The audit gives you the list of URLs and blocks missing from the page source, and in the package with fixes I move them to server rendering.

  • The audit starts at €550 one-off, the audit with the technical fixes applied starts at €950, and the monthly re-run starts at €210 per month. The difference is simple: the first gives you the report and you decide what to do with it, the second means I do the on-site work, the third tracks whether the picture moves. The number is fixed before we start.

  • The honest answer is that nobody knows in advance, which is exactly why we re-measure. Technical fixes take effect from the crawler's next pass, tidy company data tends to show up in brand recognition after a month or two, and getting into other people's roundups depends on their editors rather than on us. So I re-run the same questions and show the difference instead of quoting a date.

Read first

How this works, without the promises

Google reviews

5.0

5.0 out of 5 · 3 reviews

Write a review on GoogleAll reviews on Google
  • We received a request to develop an online store that included an AI-powered chatbot and Stripe payment integration. Everything was delivered on time, and we’re continuing to work together. I highly recommend them.
    Volodymyr Likholetovin the last week · Google
  • An excellent developer and a true professional. The work was completed strictly on time, communication was pleasant, everything was done quickly and to the point. I highly recommend him to anyone looking for a reliable, competent specialist.
    Alina Rudenkoin the last week · Google
  • A great programmer. He created an online store quickly and on time.
    Алексa week ago · Google
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