Di
Actual performance
2customers
$8MRR/mo
Did not reach leaderboard
Traction signals
Domain Rating11
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto84%84% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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.
nativeThis product was originally launched on this platform.
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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting22%22% 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, 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
Ma
Material SPA in Lisp with 500ms TTI and 11k gzipped50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Material SPA in Lisp with 500ms TTI and 11k gzipped
Hacker News12Ma
Material for MkDocs 640%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Material for MkDocs 6
Hacker News1An
Angular Material with ngRoute34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Angular Material with ngRoute
Hacker News5Ma
Material Management38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Material Management
Hacker News7MD
MDB (Material Design for Bootstrap) for Angular39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
MDB (Material Design for Bootstrap) for Angular
Hacker News3Ma
Material Design for Bootstrap 445%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Material Design for Bootstrap 4
Hacker News4Bo
Bootstrap Material Design Now Under MIT54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Bootstrap Material Design Now Under MIT
Hacker News16.
6.5 hours of Ember Screencasts48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
6.5 hours of Ember Screencasts
Hacker News7Co
Course material for numerical methods lectures at Harvard SEAS41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Course material for numerical methods lectures at Harvard SEAS
Hacker News1Emmer48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Material receiving report system
Indie Hackers1productivity