Plato is a comprehensive MLOps platform that leverages powerful open-source tools such as Feast, Kubeflow, Trino, Great Expectations, and more to cover the full spectrum of the data science lifecycle.
With Plato, teams can easily manage, track, and serve machine learning models, while also ensuring data governance and feature engineering best practices are maintained throughout the process. The platform provides a user-friendly interface that simplifies the deployment of ML models in production environments, enabling teams to focus on creating innovative and impactful models that deliver real value to their organizations.
In this documentation page, we will focus on the Feature Platform component of Plato.
MLOps Components