In the last two years, large enterprise organizations have been scaling up their artificial intelligence and machine learning efforts. To apply models to hundreds of use-cases, organizations need to operationalize their machine learning models across the organization. At the center of this scaling up effort is ModelOp, the company that builds solutions to scale the processes that take models from the data science lab into production. Even before their recent $6 million Series A funding led by Valley Capital Partners with participation from Silicon Valley Data Capital, they are already the leader providing ModelOps solutions to Fortune 1000 companies. ModelOps is a capability that focuses on getting models into 24/7 production.

The latest release of analytics startup Dataiku's platform incorporates application container and orchestration capabilities along with expanded support for deep learning libraries to help launch enterprise AI project at scale. The data platform vendor said Monday (Sept. Dataiku 5 also includes new documentation features aimed at improving application development among distributed data science teams. The New York-based data science startup joins a growing list of analytics vendors embracing cloud-native tools like Docker containers and the Kubernetes cluster orchestrator. Dataiku's spin on containerization includes combining the infrastructure tools with the in-memory processing of Python and R programing languages as well as in-memory model training and scoring.