SAS

About SAS

SAS Model Manager empowers data scientists and MLOps engineers by streamlining the analytical modeling life cycle. It offers an advanced no-code interface for model validation, governance, and deployment, enabling users to manage models efficiently, mitigate risks, and ensure responsible AI practices throughout the model lifecycle.

SAS Model Manager offers flexible pricing with tiered subscriptions, catering to diverse organizational needs. Users can explore a free trial to experience key functionalities, while those opting for premium tiers gain enhanced features, automated CI/CD processes, and dedicated support, optimizing their model management efforts and investment.

SAS Model Manager features a user-friendly interface, promoting a smooth browsing experience. Its layout highlights essential tools, ensuring intuitive navigation. Unique functionalities, like no-code validation and comprehensive monitoring, allow users to manage their analytical models efficiently, enhancing productivity and satisfaction with SAS Model Manager.

How SAS works

Users start with SAS Model Manager by signing up for an account, followed by onboarding where they learn about key features. They can effortlessly create models utilizing the no-code interface and validate them through built-in testing. The platform allows seamless integration of tools, streamlined deployment of models, and ongoing monitoring for data drift, ensuring effectiveness throughout the modeling lifecycle.

Key Features for SAS

Automated CI/CD Pipeline

SAS Model Manager features an automated Continuous Integration and Continuous Delivery (CI/CD) pipeline, enhancing efficiency. This unique aspect allows teams to integrate model updates seamlessly, minimizing manual errors and fostering a reliable deployment process, which ultimately saves time and accelerates time-to-market for AI solutions.

No-Code Model Validation

SAS Model Manager’s no-code model validation enables users to easily test and validate model scoring logic without programming skills. This feature simplifies the validation process, empowering teams to ensure model accuracy and reliability, which is critical for decision-making in analytical projects.

Model Monitoring and Explainability

SAS Model Manager includes robust monitoring and explainability tools, offering insights into data and model performance. This feature helps users detect drift and decay, allowing for proactive management and adjustments. By maintaining transparency, users can ensure models are functioning optimally and meeting compliance requirements.