A Free AI Visibility Tracker

Hacker News

It annoyed me how much all the AI tracking services were charging, so I made my own. It's free, downloadable, runs on Windows and Mac, and is a bring-your-own-API-keys alternative to the likes of Peec and Profound. It tracks AI visibility across ChatGPT, Gemini, Claude, Perplexity, and Google's AI Overviews and AI mode. It also has tools for extracting the fanout queries AI makes when searching the web. It's got dashboards and graphs and spreadsheet exports and a scheduler for anyone who wants to track visibility over time.

Visit product View on Hacker NewsJun 30, 2026

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, claude, google · Missing: agents, macos, agent

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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