Im
Actual performance
54points
45comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto61%61% 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.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive24%24% 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, revenue20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos16%16% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Im
Improving NSNotificationCenter49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Improving NSNotificationCenter
Hacker News1Im
Improving on Daniel Bernstein's Libsecded49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Improving on Daniel Bernstein's Libsecded
Hacker News1Re
Recapp'd – Improving NBA boxscores28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Recapp'd – Improving NBA boxscores
Hacker News1Re
Recapp'd – Improving NBA boxscores28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Recapp'd – Improving NBA boxscores
Hacker News3OK
OKSolar: Improving Solarized using the OKLab perceptual colorspace47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
OKSolar: Improving Solarized using the OKLab perceptual colorspace
Hacker News90Su
Submit your ideas for improving HN49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Submit your ideas for improving HN
Hacker News43Re
Reflecting on my projects to keep improving50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Reflecting on my projects to keep improving
Hacker News1Fo
Forth – Rethinking (and improving) News56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Forth – Rethinking (and improving) News
Hacker News5A
A technique for self-improving agents47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A technique for self-improving agents
Hacker News1
Outhad AI47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Improving the way you search.
Product Hunt+3