Lo
Loglast – Track the last time you did X
Hacker NewsLoglast – Track the last time you did X
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released47%47% 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, macos36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto27%27% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive26%26% 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, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
To Did List49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Track what you did, and not your almost dids'
Indie HackersWT
WTFDYUM: Why the f*** did you unfollow me?62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
WTFDYUM: Why the f*** did you unfollow me?
Hacker News7UC
UChicago admissions asked me to find Waldo. I did.63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
UChicago admissions asked me to find Waldo. I did.
Hacker News149Di
Did you ever stuck between two dresses?53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Did you ever stuck between two dresses?
Hacker News1Time-Creator.com71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
What did I do? What should I do?
Indie Hackers1productivityGP
GPTs killed my project, or did they?46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
GPTs killed my project, or did they?
Hacker News1Di
Did you know you can multiply matrices without multiplication?51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Did you know you can multiply matrices without multiplication?
Hacker News6Wh
What our Intern did in a day62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
What our Intern did in a day
Hacker News3Ol
OliveLog - keep track of your time34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
OliveLog - keep track of your time
Hacker News1Tr
Track your time between deployments38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Track your time between deployments
Hacker News3