What is generative AI (GenAI) from SAS?
SAS generative AI solutions help you use GenAI to address real business challenges. SAS connects language models with enterprise data, analytics, business processes and decisions, while providing the flexibility to choose the models and deployment approaches that fit your needs. Governance, security and transparency help you use GenAI responsibly and at scale.
Choose the right generative AI model for each business challenge
No single generative AI model is best for every business challenge. SAS gives you the flexibility to choose and combine leading foundation models, specialized language models, analytical assets and business rules to match the needs of specific tasks, workflows and business objectives.
CHOOSE FROM MULTIPLE MODELS
Match the right model to the right business challenge.
Use different foundation and specialized models based on the requirements of each task, workflow and use case.
BRING YOUR OWN MODEL
Build on the AI investments you already have.
Incorporate commercial, custom or organization-specific language models and connect them to enterprise data, workflows and decisions.
USE OPEN & COMMERCIAL MODELS
Innovate with the models that fit your strategy.
Leverage commercial, open-weight and open source models while balancing innovation, performance, governance, cost and operational control.
ADAPT AS MODELS EVOLVE
Stay flexible as technology and requirements change.
Adapt model and deployment strategies as foundation models, regulations, costs and sovereignty requirements evolve.
Connect generative AI to your enterprise data
Generative AI delivers greater value when it can work with the data and business context your organization already relies on. SAS connects generative AI with enterprise data, analytics, business rules and workflows, helping you apply AI to relevant business challenges and decisions.
Enterprise data
Connect generative AI to trusted enterprise data and business context.
Analytics & business rules
Combine generative AI with SAS analytics, models and business rules to support more relevant and actionable results.
Business workflows
Integrate generative AI into existing processes and applications rather than treating it as a standalone capability.
Govern generative AI with confidence
Build trust into the generative AI life cycle with governance, security and controls that help protect data, evaluate model performance, manage risk and support responsible AI adoption. SAS helps you govern generative AI from experimentation through deployment and ongoing use.
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Protect sensitive data with controls for privacy and security.
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Evaluate AI outputs and models to help identify risks and improve reliability.
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Manage the AI life cycle with governance and oversight from development through deployment.
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Support responsible AI with transparency, explainability and human oversight.
Extend generative AI with agentic AI
Generative AI can create content and provide answers. Agentic AI extends those capabilities by connecting AI to enterprise data, tools, analytics and business processes so AI agents can reason, make recommendations and take action. SAS helps you build and govern agentic AI solutions that put generative AI to work across business workflows.
SAS capabilities for generative AI
SAS provides integrated capabilities for developing, deploying and governing generative AI across the enterprise. Explore SAS solutions that help you work with AI models, enterprise knowledge, analytics, agents and business decisions.
SAS Viya Copilot
Bring generative AI into your analytics and development workflows.
Use AI-powered assistance to help users work with data, analytics and SAS Viya capabilities more efficiently.
SAS Retrieval Agent Manager
Connect AI agents to trusted enterprise knowledge.
Build retrieval-augmented experiences that give AI agents access to relevant information and context.
SAS Viya MCP Server
Connect AI agents to SAS capabilities.
Enable AI agents to interact with SAS analytics and capabilities through the Model Context Protocol.
SAS Intelligent Decisioning
Put AI into governed business decisions.
Combine AI with analytical models, business rules and decision flows to support consistent, governed decisions.
SAS AI Navigator
Gain enterprisewide visibility and governance of AI.
Gain a unified view of AI models, agents and use cases across your organization to help manage AI assets, align them with policies and regulations, and maintain accountability and audit readiness.
SAS Model Manager
Manage and govern models throughout the AI life cycle.
Manage SAS and open source models across the AI life cycle to streamline ModelOps and maintain model governance from development through production.
Explore generative AI use cases
Apply generative AI to the business challenges that matter most. SAS helps you use generative AI across functions and industries, from improving customer experiences and employee productivity to supporting risk management, fraud detection, compliance and business decisions.
GenAI by business function
Customer experience
Use generative AI to create more relevant customer interactions and assist employees serving customers.
Decision support
Combine generative AI with analytics, enterprise data and decisioning to help people understand information and make informed decisions.
Employee productivity
Help employees find information, generate content and complete routine knowledge-based tasks.
Fraud detection & prevention
Use generative AI alongside analytics and business rules to investigate suspicious activity and support fraud decisions.
Operations
Apply generative AI within business workflows to help streamline processes and support operational decisions.
Risk & compliance
Apply generative AI to support risk analysis, regulatory processes and compliance activities.
GenAI by industry
Explore how SAS applies generative AI to industry-specific challenges, requirements and business processes.
Recommended resources for GenAI
Meet our generative AI partners
Generative AI from SAS frequently asked questions
How does SAS approach generative AI?
SAS approaches generative AI by connecting leading foundation models with enterprise data, advanced analytics, business rules, and decisioning workflows, enabling organizations to apply GenAI to operational challenges reliably and responsibly.
How does SAS ensure generative AI outputs are trustworthy and accurate?
SAS integrates retrieval-augmented generation (RAG), built-in governance and human-in-the-loop oversight to ground GenAI models in trusted enterprise data. By combining large language models (LLMs) with analytical validation, business rules and solution offerings like SAS Retrieval Agent Manager, SAS minimizes hallucinations, protects sensitive data and ensures outputs are accurate and auditable.
Can I bring my own generative AI models (BYOM) into SAS Viya?
Yes. SAS provides an open and flexible environment that allows you to incorporate custom, commercial or open source language models (such as those from OpenAI, Google Cloud, AWS or Hugging Face). You can connect these models directly into your existing enterprise data pipelines, analytical workflows and decision flows.
How does generative AI differ from agentic AI?
While generative AI focuses primarily on creating content, text or code summaries based on user prompts, agentic AI extends these capabilities by enabling autonomous software systems (AI agents) to reason, execute multistep workflows, and take direct action within enterprise applications and business processes.
How does SAS help govern generative AI applications?
SAS provides AI governance capabilities that help organizations inventory and monitor generative AI models, track prompts and responses, assess risk, and apply security and governance controls across the GenAI life cycle. Solutions such as SAS Model Manager and SAS AI Navigator help organizations establish visibility and oversight as they develop and deploy generative AI applications.