Qu
Quickly add “Made with love in” badges to your projects
Hacker NewsQuickly add “Made with love in” badges to your projects
Share cardActual performance
1points
1comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released38%38% 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, personal29%29% 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, podcasting29%29% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%18% 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, crypto8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Nodegram41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Manage projects easily and quickly. Everything is in one pla
Indie Hackers1financeGa
Garble displayed contents of gvim quickly51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Garble displayed contents of gvim quickly
Hacker News1Re
Researching 1201 Indigenous dialects – quickly34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Researching 1201 Indigenous dialects – quickly
Hacker News2Su
Superboost – Love Hacking for OkCupid59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Superboost – Love Hacking for OkCupid
Hacker News9I
I love it Vapor-ware at its finest47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
I love it Vapor-ware at its finest
Hacker News2Ha
Hall of Fame – Show some love to your contributors45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Hall of Fame – Show some love to your contributors
Hacker News5Wh
Why We Love Giveaway (And You Should, Too)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Why We Love Giveaway (And You Should, Too)
Hacker News1We
We Love Golang33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
We Love Golang
Hacker News19Houseplant Love45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
For the love of houseplants
Indie Hackerscommitment-side-projectAd
Add badges into php projects via poser37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Add badges into php projects via poser
Hacker News1