The Advantage of Centralizing All Management of Production ML
Ensure all machine learning models and applications are managed and governed via a single controlled process across all your business units in order to avoid the risk of machine learning being loosely managed introducing endless risk and possible AI and production chaos.
Streamlining deployment into production from any machine learning Platform written in any language.
Monitoring designed and built from the ground up for the unique characteristics and sensitivities of machine learning models.
Easy access for Data Scientists and MLOps and Operations professionals to be notified and take action to ensure that models are continuously delivering expected results throughout their lifecycle.
Fully governed environments, maintaining full lineage and ensuring compliance and reducing risk from the whole process of managing machine learning in production.
DataRobot MLOps allows AI and MLOps teams to embed cutting edge predictive models in an efficient and value-driven way.
Three Key Feature Sets
Unleash the ability to work and experiment with different types of models created on any platform and in any language inside a single MLOps solution.
- Real-time predictions
- Batch predictions
- Service health monitoring
- Time series predictions
- Image and geospatial data types
- Java scoring code
- Portable docker image
Operating at Scale
Use and build upon the foundation you already have, regardless of run-time environment.
- Monitoring diverse prediction environments
- Audit logs
- Versioning and lineage
- Change approval workflows
- No-code prediction GUI
- Value and use case tracking
- Repo integration
Making Machine Learning Trustworthy
Deploy reliable, trustworthy, and unbiased models.
- Data drift analysis
- Accuracy analysis
- Anomaly warnings
- Prediction explanations
- Champion/Challenger gates into production
- Humble AI – built in mechanisms ensuring trust in your models
- Prediction intervals
The Only Scalable MLOps Architecture
Monitoring agents can get you to the scale of putting thousands and hundreds of thousands of models into production. Regardless of where your model is built — cloud, Spark, Azure, servers — you will be able to access your models from one central hub. Use what you have today and manage in one view.
Learn More About MLOps
Access the following resources to strengthen your skills and understanding of MLOps.
Take an MLOps Course
Start your journey to becoming certified in MLOps by taking a self-starter or instructor-led course.
Join the Community
Discuss MLOps and other AI-related topics with other data engineers in the DataRobot Community.
Carbon Transforms Consumer Lending with DataRobot
Today, Carbon processes 150,000 loan applications each month through DataRobot’s prediction API and tracks those deployments in DataRobot MLOps.Download case study PDF