Comet offers an Experiment Management tool designed to help machine learning teams optimize their training processes and costs by tracking all aspects of training runs, from inputs and outputs to system metrics like GPU utilization. The tool allows real-time monitoring of metrics such as loss and accuracy, enabling early stopping of underperforming experiments to save resources. It also acts as a repository to prevent duplication of experiments by allowing users to compare current runs with previous ones through features like diff mode. Comet supports distributed training and hyperparameter optimization, providing tools to organize and schedule experiments efficiently, thereby narrowing the search space and reducing unnecessary costs. The platform's ease of integration into existing workflows aims to enhance productivity while managing cloud training expenses effectively.