Absolutely. Codemonkey.ai analyzes every source code commit and correlates each with an issue tracking system to understand when defects are introduced, featur

Absolutely. Codemonkey.ai analyzes every source code commit and correlates each with an issue tracking system to understand when defects are introduced, features added, etc. We build a predictive model using the prior commit history as a training set to predict the risk of new commits going forward. This model leverages over 50+ metrics that we derive from each commit. With this model we can do the following: * Correlate code commits/changes to features, stories, and work items to understand the quality and risk impact that those things have on the codebase * Utilize clustering to provide insights around developer productivity and quality impact to the codebase * Utilize clustering to help with sizing of future features based on historical actuals These are just a few of the areas where we are using ML within Codemonkey.ai today. In the future our goal is to tie additional information from production environments into this model as well.