Bring your machine-learning applications to production

Log all data, models and artifacts and track all code execution

Read and transform data from batch and online data stores

Train models at scale with automated testing functions

Deploy real-time pipelines for data collection, model serving and monitoring

Automate model monitoring and drift detection

Turn your Python code to composable functions, that can run at scale on Kubernetes, Dask, and Horovod in a single command. Leverage a function marketplace to accelerate your model development process

Deploy real-time pipelines for data collection, model serving and monitoring