SAS Democratizes AI with Enhanced Viya Platform and Governance Tools
SAS, at its Innovate conference, announced a series of AI-focused offerings across its portfolio. These include enhancements to its Viya platform, new custom AI models for specific sectors, and governance resources to help organizations mitigate AI-related risks. The aim is to democratize AI by making it more accessible and manageable for a wider range of users.
SAS Viya and AI Agents
SAS has introduced new and enhanced components for the SAS Viya platform, targeting both developers and end users.
SAS Data Maker: Synthetic Data Generation
SAS Data Maker, a synthetic data generator, helps organizations overcome data privacy and scarcity challenges. Enhanced with technology from the acquisition of Hazy, it analyzes source datasets, determines their structure, and creates an entity relationship map. This map is then used to train a generative model for producing high-quality synthetic data.
The latest version of Data Maker supports multi-table and time-series data. Currently in private preview, it is expected to be generally available in the third quarter of this year.
SAS Viya Intelligent Decisioning: AI Agent Deployment
SAS Viya Intelligent Decisioning enables users to build and deploy intelligent AI agents using a low-code/no-code tool. This tool balances AI autonomy with human involvement, optimizing oversight based on task complexity, risk, and business goals. For instance, an agent vetting mortgage applications can flag specific denials for human review, allowing the human to query the agent's reasoning and make the final decision.
SAS Viya Copilot: AI-Driven Conversational Assistant
SAS Viya Copilot, currently in private preview and built on Microsoft Azure AI Services, is an AI-driven conversational assistant embedded within the SAS Viya platform. It assists developers, data scientists, and business users by accelerating analytical, business, and industry tasks. The initial Copilot offering in Model Studio includes AI-powered model development and code assistance for SAS users and will be generally available in the third quarter.
SAS Viya Workbench: Enhanced Development Environment
Initially released in 2024, SAS Viya Workbench now supports R language coding and offers SAS Enterprise Guide as an optional integrated development environment (IDE). It is also available on Microsoft Azure Marketplace and AWS Marketplace.
Robert Kramer, VP & principal analyst, Enterprise Data, ERP & SCM, Moor Insights & Strategy, noted that these updates integrate features with built-in governance and ready-to-use models, which are crucial for enterprise use. He added that customers may benefit from faster onboarding, easier collaboration, and more secure AI development, especially in regulated industries where auditability and model transparency are essential.
Prebuilt AI Models
SAS has also introduced several new AI-based offerings, including six custom AI models designed for specific processes in various industries.
According to Udo Sglavo, VP of Applied AI and Modeling, SAS's customer base is divided into two segments: those with data science teams and those without. The new models address the needs of both segments. Companies with data science teams can focus on strategic questions, while those without can quickly start and see the impact of AI on their business models.
The initial models include AI-driven Entity Resolution and Document Analysis (suitable for many industries), Medication Adherence Risk (healthcare), Strategic Supply Chain Optimization (manufacturing), and Payment Integrity for Food Assistance and Tax Compliance for Sales Tax (public sector).
Later this year, four more models will be added: Fraud Decisioning for Payments and Card Models (banking), Payment Integrity for HealthCare (healthcare), Worker Safety Monitoring (manufacturing), and Tax Compliance for Individual Income Tax (public sector).
Sglavo emphasized that these models are lightweight, easy to deploy, and built around real-world industry cases, allowing users to quickly productionize them and gain value.
Kramer agreed, stating that the availability of pre-built AI models for applications like fraud detection, supply chain planning, and health risk assessment should help organizations accelerate their AI adoption by providing ready-to-use solutions.
AI Governance
As AI becomes more pervasive, the need for governance to manage associated risks also increases.
Reggie Townsend, VP of the data ethics practice at SAS, emphasized the importance of assessing intended use and expected outcomes before deployment and monitoring for ongoing compliance. This involves oversight, operations, and organizational culture, all of which contribute to AI governance. The goal is to balance the productivity benefits of AI with potential inaccuracies, inconsistencies, and intellectual property leakage.
SAS has introduced new governance resources, including the AI Governance Map, to help organizations assess their AI governance maturity in oversight, compliance, operations, and culture. Additionally, SAS plans to release a unified holistic AI governance solution for executives to aggregate, orchestrate, and monitor AI systems, models, and agents.
Abhishek Punjani, research analyst – AI at Info-Tech Research Group, praised SAS's direction, noting that many organizations initially prioritized innovation and speed over control in their AI journey. He believes the industry is shifting towards a more responsible and balanced approach, and SAS is at the forefront of this movement with its latest AI innovations.
Punjani also highlighted the expansion of the Viya platform with tools aimed at practical AI enablement. SAS Data Maker addresses data scarcity and privacy by generating secure synthetic data, while SAS Viya Intelligent Decisioning enables organizations to build AI agents with customized human involvement.
He concluded that these solutions mark a shift toward more grounded, enterprise-ready AI, reflecting a growing focus on control and accountability. As organizations seek to move beyond experimentation, approaches like SAS's, which build governance and flexibility into the product itself, are reshaping mainstream AI adoption.
