Pe
Personal entertainment assistant
Hacker NewsPersonal entertainment assistant
Here's a Youtube demo: https://www.youtube.com/watch?v=X4e5t_d0_ig The assistant was built on top of our recommendation engine. Sit back and listen to your entertainment assistant (I really mean it!) - it's still flaky if you don't have any friends or didn't "kwix" (share/rate) anything, I'm really open to any suggestions you have! P.S: Sorry for the video quality. Also the voice is Siri and is really in the app, that's not a cheap voice over :D.
Share cardActual performance
1points
2comments
Did not reach leaderboard
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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive58%58% predicted probability of success on AppSumo, 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 · Missing: supports, reddit linkedin, podcasting55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal, video · Missing: mobile apps, ios, entrepreneurs51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos33%33% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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