Actual performance
214upvotes
4comments
Made the leaderboard
Traction signals
Makers1
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: openclaw, open · Missing: mac, agents, macos71%71% predicted probability of success on Product Hunt, 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, personal42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto34%34% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting33%33% 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, intuitive28%28% 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, revenue27%27% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released20%20% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
AppTruth45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
See what your app really does
TrustMRRArtificial Intelligence
OpenClaw70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The AI that actually does things
Product Hunt+836Open SourceI
I made An AI assistant that does things, not just suggests them30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I made An AI assistant that does things, not just suggests them
Hacker News6Th
This AI Does Not Exist58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
This AI Does Not Exist
Hacker News434Tr
Truck Does Not Exist73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Truck Does Not Exist
Hacker News3Th
This Dick Does Not Exist73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
This Dick Does Not Exist
Hacker News25Th
This Wojak Does Not Exist73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
This Wojak Does Not Exist
Hacker News30Mo
Mountain Does Not Exist73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Mountain Does Not Exist
Hacker News7Th
This Synth Does Not Exist73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
This Synth Does Not Exist
Hacker News2Ho
How many seasons does Melbourne (VIC) have?45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
How many seasons does Melbourne (VIC) have?
Hacker News1