Launching today
Findabl
Know when AI recommends your brand, using real citation data
4 followers
Know when AI recommends your brand, using real citation data
4 followers
Findabl sends real prompts to ChatGPT, Gemini, Perplexity, and Claude, then captures the responses, brand mentions, competitor citations, and publisher domains behind each recommendation. See whether AI cites your brand, who it cites instead, and how citation frequency changes over time. No modeled scores. Direct, auditable measurement.
Hi Product Hunt, Thorsten here.
Findabl started with a question we couldn't answer for our own clients: when a buyer asks ChatGPT for a recommendation in your category, do you come up?
Every tool we tried answered something else. Most put the client's name in the prompt. Ask "is Acme any good" and of course it says yes. That's not visibility, that's politeness. Others sold us AI keyword volume, which can't exist. No AI company publishes query data.
So we ask the question a buyer would ask, with your name nowhere in it, across ChatGPT, Gemini, Perplexity and Claude. You get every response back verbatim, who got named instead of you, and which publisher domains the engine built its answer from.
Three things we don't do.
We track four engines. Some tools claim ten or more. We'd rather do four properly.
We can't tell you what everyone types into ChatGPT. Nobody sees all of it. A consented panel gets you closer, and the good ones say so, but a panel is still the people who joined it.
And we put a margin of error on every number. Ten questions across four engines is forty data points. That's small. We won't call a change real until it clears the margin, which sometimes means telling you we don't know yet.
One thing I'd genuinely like to know from this crowd: if you've tried to measure this, what did you end up trusting, and what made you stop?
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