SAS Model Manager Features List
Unify model assets
- Establish a secure and versioned model registry. Enable your team to understand your projects, models, metadata and supporting artifacts.
- Profile, tag, sort and categorize your modeling assets. Search and discover models across your organization.
- Access models and artifacts using the user interface or programmatically through REST API, SAS code or Python code to integrate with automated MLOps processes.
- Manage, version, score and govern SAS, Python, R and other models across your enterprise.
- Audit major events including model creation, deletion and deployment.
- Read the blog to learn more about versioning in SAS Model Manager.
Validate models
- Automatically generate scoring code for Python and R models using the sasctl package.
- Ensure models run within SAS Model Manager and production environments.
- Compare SAS, Python and R models side by side to determine the best fit for production.
- Read the blog to learn how to register Python models using a new step in SAS Studio.
Deploy models in minutes
- Deploy SAS, Python and R models across a variety of destinations, with no recoding.
- Deploy models in the cloud, on premises, in Snowpark or in Azure Machine Learning to be included in databases like Teradata.
- Publish SAS, Python and R models into containers saved on registries within the cloud or on premises.
- Read our guide to deploying models using CAS.
Monitor, detect, alert and repeat
- Illuminate data, concept and model drift with ongoing monitoring.
- Gain dynamic performance reporting with out-of-the-box reporting from deployment to retirement.
- Track, validate and audit reports to select champion models for use in other applications.
- Synchronize KPIs to alert stakeholders or cue model retraining, minimizing costly downtime.
- Customize performance reports and create your own KPIs based on model performance data.
- Read our guide to monitoring natural language processing models within SAS Model Manager.
Streamline MLOps processes
- Use templates to create repeatable Continuous Integration and Continuous Delivery (CI/CD) processes to efficiently test and promote new models and decision flows.
- Integrate multiple environments, tools and applications through our flexible API ecosystem.
- Automate, integrate, promote and keep the right people informed with an adaptable workflow ecosystem.
- Read the blog to learn how to leverage a CI/CD Promotion template using SAS Model Manager.
