At 10Clouds, we use MLflow, an open source library that offers a full-cycle machine learning platform, making it easy to develop, deploy, and share models. It offers a set of APIs that work with any library (TensorFlow, PyTorch, XGBoost, etc.) and in any environment, including the cloud.
MLFlow records and tracks training runs and model artifacts, which helps the DS team to track the experiments and for the client to see the progress. The MLflow library also has a built-in Model registry, which serves as storage for all production ready ML models.