Open source software from SAS
From data to insights. Faster. Help build the future of AI and analytics with open source tools from SAS Institute Inc.
From data to insights. Faster. Help build the future of AI and analytics with open source tools from SAS Institute Inc.
Browse some of our most popular open source projects. Contributions welcome.
A library for synthetic tabular data generation with rich functionality and end-to-end differential privacy guarantees.
The SAS Agentic AI Accelerator provides a way of building AI agents leveraging SAS Viya technology.
The SAS generics library for Go provides packages that leverage generic types to support various common development tasks and patterns.
Application to score models and decisions deployed in the SAS Micro Analytics Service.
A community-driven repository for documents and tools to help you architect, implement, and operate your Viya® environments. Join the community and collaborate to create supporting materials for quickly and consistently achieving value.
Browse the SAS Software organization on GitHub. Read the SAS Open Source Contributor Handbook to get started.
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Create custom interfaces for SAS® Studio on SAS® Viya®. Customize, save, and share with other users at your site.
Construct and manage customer journeys across all engagement channels in a flexible and secure manner. Open source resources from SAS help you do more.
Streamline your SAS deployments with open source tools.
Open source Terraform configuration files for provisioning SAS® Viya® resources on public clouds.
Setup and deployment instructions for using SAS® Retrieval Agent Manager multiple platforms.
A Model Context Protocol server for executing SAS code on SAS Viya environments.
The SAS Extension for Visual Studio Code provides support for the SAS language, including features such as SAS syntax highlighting, code completion, hover help, code folding, outline, SAS code snippets and run SAS code.
Purpose-built for developers and modelers, SAS® Viya® Workbench is a self-service, on-demand compute environment for analytical development, including building AI and machine learning models for better data analysis.
Experiment with comprehensive, industry-specific demonstrations of Workbench capabilities.
Determine whether your third-party, open source dependencies are compatible with Workbench.
Artificial intelligence systems designed, developed, and deployed with human-centricity in mind—systems that incorporate appropriate levels of accountability, inclusivity, transparency, completeness, and robustness to promote human agency and prevent human harm. Trustworthy AI aims to ensure safety, reliability, and ethical considerations.
Steps for evaluating and deploying a more trustworthy AI system.
Python notebooks and SAS programs that demonstrate key principles of trustworthy AI.
Explore →A library of SAS code examples. Copy and execute programs in an environment you choose.
Build applications that integrate the SAS AI and analytics platform with open source tools and frameworks.