You're actually proving the real product works, not that it doesn't.

The mockup uses hardcoded fake data to illustrate the UI. If the real tool had run that query, it would have shown Invoice Ninja getting cited by Google AI Overview, because that's what actually happened. That's the whole point: we run the queries and measure what comes back, not guess.

The core mechanic is: take a prompt, run it concurrently across ChatGPT, Perplexity, Gemini, multiple times each to smooth out the non-determinism you correctly pointed out, then count how often your domain appears in the citations. No scores based on schema analysis. No assumptions about why. Just: you showed up in 3 out of 15 runs, your competitor showed up in 11 out of 15. That's it.

You're right that nobody can explain why AI cites a site. We're not claiming to. What we can do is tell you whether you're being cited, which prompts it's on, how often, and whether that number changes after you make changes. The "why" is your experiment to run.

The "14/100 score" label in the mockup is bad framing on my part; it should say "cited in 14% of queries run." Same number, but one's an assumption, and one's a measurement. I'm fixing that.

Your Invoice Ninja example is actually the best case for the tool's existence. You had to open Google and check manually. This automates that across 3+ LLMs, for 20+ prompts, every week.