We
We made a fast audio editor for podcasting
Hacker NewsWe made a fast audio editor for podcasting
Share cardActual performance
154points
64comments
Made the leaderboard
Launch Intel predictions
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BetaListSuited for BetaList early-adopters · Strong signals: audio · Missing: web3, chat, crypto86%86% predicted probability of success on BetaList, 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: podcasting · Missing: supports, reddit linkedin, created77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive45%45% 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, revenue24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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