Simplified model deployment - Data scientists use a variety of languages, frameworks, tools, and IDEs. With MLOps, ML teams can develop models using the interface, framework, and language that makes the most sense for the task at hand. For example, transitioning from a prototype model in a Jupyter Notebook to a large-scale hyperparameter sweep should be trivial.