Findabl
Know when AI recommends your brand, using real citation data
What it does
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. Launch code PRODUCTHUNT gets one free full scan at findabl.app/producthunt.
See which AI engines cite your competitors instead of you. Track citations across ChatGPT, Perplexity, and Gemini. Free citation score in 60 seconds.
Findabl is an AI citation intelligence platform that measures where ChatGPT, Perplexity, and Gemini cite your brand versus competitors, then delivers prioritized Actions to close the gap. Written so your team can ship the fixes next week, not next quarter. Honest baseline. Real recommendations grounded in your own data. Every action item carries the observation that triggered it and the test you'll run to know it worked. Common options include Sustivex LAI , Norexa Monthly , and Lurevex . Dosing intervals range fr AI engines recommend brands they can retrieve, verify, and trust. We build that footprint. Build a consistent presence across the trusted sources AI engines retrieve from.…from findabl.app
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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