When I launched Luxcerta, I did the obvious vanity check: I asked an AI what it knew about my company.
Gemini, with web grounding on, decided "Luxcerta" was most likely a typo for LuxCarta — a French geospatial-data firm that has been around for decades. When I asked specifically about luxcerta.com, it suggested the domain was "possibly a parked domain or a phishing site."
That stung. But it was also the single most useful data point I could have asked for — because measuring exactly this is what Luxcerta does. So I turned the tool on myself and wrote down the numbers.
One line: Luxcerta measures how AI models talk about a brand. Not your Google ranking — your standing inside AI answers. When someone asks ChatGPT, Claude, or Gemini a question in your category, are you named, skipped, or misquoted? We count it with a fixed method you can reproduce yourself.
Nothing fancy, and that's the point — the whole pitch is that you can repeat it. 5 identity questions about the brand ("What is Luxcerta?", "What does luxcerta.com do?", and variants), each asked twice in a fresh conversation (AI answers vary run to run; a single answer means nothing). Gemini with grounding (its live web-retrieval mode). Count mentions and citations of my own domain with plain string matching — no AI judgment in the counting.
| Metric | Count | |---|---| | Answers that mentioned Luxcerta (the real one) | 0 / 10 | | Answers that cited luxcerta.com | 0 / 10 | | Answers that retrieved my site at all | 0 / 10 |
Zero across the board. Worse than zero, actually: the name was being actively reassigned to an established company with a near-identical spelling, and my domain was being guessed as hostile.
The same day, Google Search's AI Overview — a different product, different retrieval pipeline — already described Luxcerta correctly: "an independent studio that focuses on GEO monitoring." It had eaten my homepage's meta description and structured data and got it right.
So on one single day, from one company: Google Search's AI knew exactly who I was, and Gemini's grounded answers thought I was a typo. Two AI surfaces, opposite verdicts, same underlying brand.
That gap is the phenomenon the product measures. "Is AI right about you" has no single answer — it has one answer per surface, and they disagree more than anyone expects.
I wanted the grounded models to have something authoritative to retrieve, so I gave them a few crawlable, machine-readable anchors that all agreed on one definition of the entity: Organization structured data (schema.org JSON-LD) on the homepage: legal name, founder, sameAs links tying the domains together. A tightened meta description stating plainly what the company is. A GitHub profile page as an independent, high-authority node repeating the same one-line definition — and one explicit line disambiguating Luxcerta from LuxCarta. Search Console: submitted the sitemap and requested a recrawl so the fresh signals got picked up quickly.
Honesty note, because it's the whole brand: I changed several things at once and then watched. This is a case study of one brand over one week, not a controlled experiment. I can tell you the inputs and the measured outputs; I can't hand you a clean attribution to any single lever.
One week later, the same identity query on Google's AI Overview returns, stably:
Luxcerta is an independent studio that focuses on GEO Monitoring, which measures how artificial intelligence platforms talk about and represent a brand.
No more LuxCarta. The knowledge panel points at my own "Our Name" page. Organic result #1 is the site. The reassignment to the French firm is gone from that surface.
Roughly a week, from "probably a typo / possibly phishing" to a correct, stable, one-sentence definition — with no backlinks bought and no PR, just a handful of crawlable nodes that agreed on who the entity was.
I'm a brand-new company, so my invisibility is unsurprising. But the exact same mechanism hits established local businesses that simply have a low signal footprint online — and there the stakes are real.
In our first public category survey — dental implant clinics in greater Taipei, 15 real user questions × 3 fresh conversations each, 45 answers per platform — the clearest finding was this: the AI reads a clinic's own website, then recommends a different clinic. In the same answer, it cited clinic A's site as a source and put clinic B on the recommendation list. The content got consumed as category reference material; the credit went elsewhere. Run the same questions on ChatGPT, Claude, and Gemini and you get three almost non-overlapping lists. (The full survey is here.)