EazyML's target audience encompasses organizations that are actively involved in developing and deploying machine learning models at scale. This includes technology companies, financial institutions, healthcare providers, retail businesses, and any enterprise that leverages data science for competitive advantage. More specifically, the target audience comprises teams and departments that build, manage, and deploy ML models, such as Data Science Teams, Machine Learning Engineering Teams, AI/ML Product Teams, and MLOps Teams. These organizations are likely experiencing challenges related to ML model lifecycle management, including issues with reproducibility, collaboration, deployment complexity, model drift, and operational inefficiencies. They are looking for a comprehensive platform that can centralize their ML operations, automate repetitive tasks, and provide end-to-end visibility and control over their models from development to production. The platform is designed for businesses that are looking to industrialize their ML efforts and move beyond ad-hoc model development.