Codehawk
Code monitoring tool to keep track of risk areas
Most software development teams take on board compromises and trade-offs over time and accumulate legacy code that could be a risk to their product. Codehawk exists to help track these problems and protect dev time.
Share cardActual performance
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Launch Intel predictions
Analyze your own launch →63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
17%17% predicted probability of success on AppSumo, based on ML models trained on real launch data.
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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