Streamline model deployment and management with a single tool that lets you operationalize AI everywhere.

Streamline the model life cycle. Deploy models everywhere. Connect data scientists and IT. And get the most value from your analytics investments.

Ensure model governance and transparency.

A centralized, searchable repository for all types of models and analytical assets gives you complete visibility into your analytical processes, ensuring traceability and governance. The solution simplifies model management with life cycle templates and version control, enabling you to track project history through each step of the model management process and get a unified view of each model’s currency, definition and value. Using open REST APIs to access models and model-score artifacts streamlines IT work.​

Easily validate models to ensure high-quality predictions.

SAS Model Manager automatically generates executable scoring code for Python-based models.​ You can easily test models, validating model scoring logic before models are pushed into production using a precise methodology and a system that automatically records each test the scoring engine performs.

Build once, deploy everywhere – no additional testing required.

Efficiently move your analytical models from the innovation lab into your chosen production. With SAS and Microsoft , you can now easily and seamlessly deploy models in Azure Machine Learning (AML).

Automatically monitor model performance to keep them performing as expected.

SAS Model Manager automatically monitors model performance from inception, to usage, to retirement, regardless of the language used to create them. Performance benchmarking reports display the champion model’s scoring performance and document conformity to required standards. Alerts are generated to indicate model decay. As models are used across different departments, the solution produces extensive tracking, validation and auditing reports, and marks champion models for use in other applications. Ongoing monitoring lets you know when it’s time to refine or retire a model.

Increase efficiency by adapting models to reflect internal or external changes.

Continuously update models to keep pace with changing market and business conditions. You can retrain the existing model on new data, or revise the model using feature engineering or new data elements. Model retraining integrates with the model pipeline processing environment for greater efficiency.

Save time and resources by automating the model life cycle using a CI/CD approach.

SAS Model Manager enables you to integrate multiple environments, tools and applications using open REST APIs. You can automate the analytic life cycle by creating custom workflows that match your business requirements and processes.

Free Trial

Try the latest SAS® Viya® capabilities

Get a free, 14-day trial of SAS® Viya, which includes all the capabilities of SAS® Model Manager as well as for the entire analytics life cycle.


Simplify model collection creation and management with a web-based interface that easily automates the model management process.

Data access, preparation & quality

Access, profile, cleanse and transform data using an intuitive interface that provides self-service data preparation capabilities with embedded AI.

Custom chatbot creation

Create and deploy custom, natural language chatbots via an intuitive, low-code visual interface for chatbot-enabled insights and conversational user experiences​.

Data visualization

Visually explore data, and create and share smart visualizations and interactive reports through a single, self-service interface. Augmented analytics and advanced capabilities accelerate insights and help you uncover stories hidden in your data​.

Centralized & searchable model repository

Easily manage analytical models via a centralized, secure web-based repository. Prebuilt model life cycle templates let you manage projects collaboratively.

Task automation with custom workflows

Define and track custom workflows for model life cycle management, including all phases – from problem-statement creation to model development and utilization.

Build once, deploy everywhere

Easily deploy models into your business processes in just a few clicks with rapid, automated model deployment – in batch or real time, in the cloud or at the edge.

Programming only interaction through REST APIs

Lets you use REST APIs to access, compare, assess and score models.

Powered by SAS® Viya®

SAS Viya has a completely redesigned architecture that is compact, cloud native and fast. Whether you prefer to use the SAS Cloud or a public or private cloud provider, you'll be able to make the most of your cloud investment.

Cloud Providers

Conquer all your analytics challenges – from experimental to mission critical – with faster decisions in the cloud. The latest release of SAS Viya is now available on these cloud providers.

SAS Cloud

Running the latest version of SAS Viya natively on Microsoft Azure, the SAS Cloud manages your entire analytics platform for optimal performance and value.


Microsoft is our strategic partner and preferred cloud provider. With deep integration and a shared road map, SAS and Microsoft are shaping the future of AI and analytics in the cloud.


Designed to be cloud-native, SAS Viya is tested and approved to leverage the same cloud services used by millions of AWS users.


With a commitment to innovation and open-source cloud principles, SAS Viya brings native AI and advanced analytics to Google Cloud.

Red Hat OpenShift

SAS Viya is bringing the latest DataOps, AI and ModelOps capabilities to Red Hat OpenShift – the leading enterprise Kubernetes platform, built for your open, hybrid cloud strategy.​

SAS is adaptable through the choices it affords in techniques, data sources, deployment and even programming languages, while also delivering the speed and scalability that allows us to control outcomes. USG logo Paul Reed Principal Technical Manager USG

Explore More on SAS® Model Manager & Beyond


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What's New in SAS Model Manager

Find out about new features and capabilities of SAS Model Manager in SAS Communities.


Model Deployment & Management: What You Didn’t Learn About Machine Learning in School

Learn how to get the most value from machine learning with automated, collaborative model management and governance.


Mastering the Model Life Cycle Orchestration Journey

Learn about best practices for machine learning in production.

Interested in SAS® Model Manager on SAS® Viya® 3.5?

Connect with SAS and see what we can do for you.