DataRobot MLOps realized the real value of AI for business units and departments while reducing the time-to-market. MLOps streamlines model deployment, closing the gap between data science and engineering teams, making AI models more readily available for the business.
Analyze the accuracy and performance of all of your deployed AI models in real-time. Properly monitoring deployed models using relevant machine learning KPIs is critical to ensuring that their performance always stays high. With MLOps monitoring in place, your teams can deploy and manage thousands of models and be ready to scale AI in production.
Deployed models need to be updated frequently and seamlessly to ensure their continued business impact. Managing, retraining, and replacing models is easy with MLOps model lifecycle management that supports testing and warm-up of replacement models and A/B testing of new models against older versions, and seamless rollout of updates.
Having full access, auditing, and tracking control over the models is necessary to minimize risk and ensure compliance with regulators. MLOps provides the integrations and capabilities you need to ensure consistent, repeatable, and reportable processes for your production models.
With MLOps, we were able to deploy both DataRobot and non-DataRobot models within minutes rather than weeks, enabling us to achieve a far faster time to value than with homegrown deployments. In addition, the monitoring capabilities ensure that our models are generalizing appropriately to new data. We have so far had 100% uptime on our deployments.