Our own AI visibility score is 0

01

What we measured

We sell AI visibility measurement, so the first brand we measured was our own. On 19 September 2026 we put eight buyer questions to Perplexity through its API and analysed the answers with the same code a customer’s report runs on.

On 1 October 2026 we asked the same eight questions again. Both times, Bungad was named in 0 of 8 answers. Mention rate 0%. Citation share 0.0%. No average position, because we never appeared. Visibility score: 0. The score did not move. The sources the engine cited did, and both are set out below. We ran the September audit twice to be sure and the October one once, and kept all three records; every figure on this page traces to one of them.

We know of no other vendor in this category that publishes its own audited number, and we understand why: ours is the worst one possible. We are publishing it anyway, for three reasons:

• It proves the measurement is real rather than a marketing graphic.
• It shows you exactly what a client report contains, including the parts that sting.
• It starts a public before-and-after that we will update every month on this page. This is the first of those updates.

02

The numbers, month by month

The newest run is the first column. The two September runs gave the same result on every row except the last, so they share a column and that row names each.

Swipe sideways to see every column

What changed since September, and what did not

What did not change: the score, 0 out of 100; the number of answers naming us, 0 of 8; the engine; and the eight questions, which were asked word for word. Twelve days on, the score is where it was. That is a real zero twice, and we would rather print it twice than wait for a better month.

03

The eight questions

These are fixed. We asked exactly these on 19 September and again on 1 October, and we will ask them again next month, so the comparison means something. Every one of them, in every run, returned an answer that did not contain the word Bungad.

Swipe sideways to see every column

04

Who got named instead

We track six rivals by name. The count is the number of answers, out of eight, in which our analysis code found each name: the same code, and the same count, that a client report uses. The two September runs produced their column identically, naming the same brands in the same answers. In every run the code found all of its mentions in the answers to questions 2, 5 and 8, and none in the other five. The sixth rival we track, Palmata, was counted in none.

05

The domains Perplexity cited on 1 October

This is the most useful output of any audit, ours included: the sources the engine drew on while answering questions about our category. The October figures come from the stored record of the 1 October 2026 run, which contains 135 citations across 62 distinct domains. Not one of them was bungad.com.

Swipe sideways to see every column

06

The domains Perplexity cited on 19 September, run A

The September result, kept as we first published it. The figures below come from the stored record of run A, the first of two runs on 19 September 2026, which contains 90 citations across 74 distinct domains. Not one of them was bungad.com.

The citation list moves between runs. The score did not.

On 19 September we ran the same eight questions twice, about a minute apart, and stored both: run A above and run B. Every headline number was identical — 0 of 8 named, 0% mention rate, 0.0% citation share, no average position, score 0 — and both runs named exactly the same competitors in exactly the same answers. The citation counts did not hold still:

07

What we are doing about our own zero

The same four things we would put in a client’s plan, in the same order, against the same questions.

1. A direct answer page for each question we lose. Eight questions, eight pages, each titled with the question and answering it in the first two sentences. This page is one of them.
2. Our specifics in plain text on our own domain. $99, $299 and $799 per month, the engines we actually cover, what we do not track. Text on a page, not a pricing image and not a PDF — because peec.ai being the second most-cited source in run A shows a vendor page can be quoted when it states facts plainly.
3. An accurate presence on the domains above. Business directories and category roundups first, since those are what the engine reached for when it did not reach for a vendor.
4. Re-run the same eight questions monthly and publish the new number here, up or down. A score that only ever gets published when it improves is not a measurement.

08

How to check this yourself

The run is a script in our repository, not a spreadsheet we maintain by hand. It asks the eight questions above through the configured engine APIs, analyses each answer with the same functions that produce client reports, and writes a complete JSON record of the run — every answer, every citation, the metrics — so a number on this page traces back to a file that exists. The command:

npm run self-audit

09

Why publish this at all

Because the alternative is asking you to trust a number we will not show about ourselves. Every claim on this site is checkable: the questions are listed, the method is a command you can read, and the result is the worst one available. If our measurement flattered anyone, it would have flattered us first.

Next update: November 2026, same eight questions, published here whichever way it moves.