Bo
Borel, on-demand data analysis in 24 hours
Hacker NewsBorel, on-demand data analysis in 24 hours
Share cardActual performance
3points
1comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto61%61% 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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive42%42% 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, personal38%38% 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, revenue14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
ManyData29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
On Demand Data Analysis
Indie Hackers1b2bCo
Consume an idiom, one in every 24 hours52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Consume an idiom, one in every 24 hours
Hacker News124
24 hours && 24 red bulls52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
24 hours && 24 red bulls
Hacker News17Br
Brainwave Data on Demand50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Brainwave Data on Demand
Hacker News3Ou
Our first OSX app, FontPrep, free for 24 hours50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Our first OSX app, FontPrep, free for 24 hours
Hacker News2Pr
Productizebook.co – A book I wrote in 24 hours61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Productizebook.co – A book I wrote in 24 hours
Hacker News6He
Healer – On-demand AI clinicians in your pocket 24/737%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Healer – On-demand AI clinicians in your pocket 24/7
Hacker News2Iris33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Open: 24/7 / 24 hours, 7 days
Indie Hackerscommitment-full-timeA
A Codecademy for data analysis (with R)32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A Codecademy for data analysis (with R)
Hacker News2Ne
Newbies exploring Topological Data Analysis with R35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Newbies exploring Topological Data Analysis with R
Hacker News2