Over the past two years, there has been a notable increase in investment toward machine learning initiatives, prompting Stakion to focus on building a product that emphasizes granular monitoring and actionable insights for effective model performance evaluation. Stakion's approach requires data science teams to access diverse metrics and tools to identify and address model issues, leading to its recent integration with Comet. By joining forces with Comet, Stakion aims to enhance machine learning production monitoring by bridging experimentation and production, providing comprehensive visibility of model lifecycles, and enabling teams to track and adapt models to prevent recurring issues. This collaboration is positioned to offer a unified platform for data science teams to improve the reliability and performance of machine learning models.