H2O Driverless AI delivers enterprise-ready, scalable, and secure AutoML that can run on any cloud platform or in on-premises environments, using the architecture that this document describes. With an on-premises environment, you do not need to move your data to the cloud; you can perform AutoML securely wherever your data resides.
H2O Driverless AI enables data scientists to work on projects faster and more efficiently by using automation to perform key machine learning tasks in minutes or hours, not months.
H2O Driverless AI increases the productivity of data practitioners by automating data processing, feature engineering, model building, and hyper parameter tuning. It is a stand-alone platform that can be applied for use cases such as Natural Language Processing (NLP), time series forecasting, and image classifications. Enterprises can choose to deploy an MLOPs platform to enable cross-functional collaboration and to manage the end-to-end life cycle of their AI applications. In those cases, users can integrate H2O Driverless AI with their MLOps platform such as cnvrg.io (see Invoking H2O Driverless AI from cnvrg.io MLOps Platform).