Pa
Actual performance
1points
1comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto73%73% 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 NewsStrong engagement from HN community · Missing: https docs, excited, just released62%62% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos46%46% 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, personal42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive34%34% 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, revenue21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting20%20% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Pa
Papers-I-read62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Papers-I-read
Hacker News6Re
Read ArXiv papers 2x faster71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Read ArXiv papers 2x faster
Hacker News1
Rabbit53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Read arXiv Papers 2x Faster
Product Hunt+9Th
The “tl;dr” of Recent Transformer Papers58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The “tl;dr” of Recent Transformer Papers
Hacker News5Th
The Federalist Papers, typeset as the 1787 newspapers they ran in67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Federalist Papers, typeset as the 1787 newspapers they ran in
Hacker News58Ba
Back Me Up – Find papers that back your argument63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Back Me Up – Find papers that back your argument
Hacker News2Sc
Scipion – Read research papers with zero overhead58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Scipion – Read research papers with zero overhead
Hacker News3Ar
Arxiv Reader: Search and Read Arxiv Papers67%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Arxiv Reader: Search and Read Arxiv Papers
Hacker News1
PagePeek59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Your AI Professor for drafting and evaluating papers in secs
Product Hunt+6Papers.Chat28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Read, summarize, and discuss academic papers from any field.
Indie Hackerscommitment-side-project