ChronoFlow
Never run out of prepaid hours again
I created Chronoflow to fill a gap that I had in my freelancing client retainer hour tracking. Client required monthly reporting of what they had left and it was a process to get the information they needed.
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Launch Intel predictions
Analyze your own launch →62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
40%40% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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