SAS Clinical Acceleration on Viya helps life sciences teams scale clinical submissions by automating derivations, embedding validation, and producing submission-ready outputs within a governed, cloud-native environment.
Learn how the SAS Agentic AI Accelerator and SAS Viya can be used to build a governed, multi-agent support-ticket solution that combines text analytics, RAG, LLMs, business rules, and human oversight to improve resolution speed, accuracy, and operational efficiency.
Explore how SAS AI-Driven Entity Resolution on SAS Viya combines no-code configuration, probabilistic matching, and industry-specific integrations to create trusted identities, improve data quality, and support critical decisions across sectors such as public services and financial crime prevention.
This post explores how Agentic AI and LLMs can help reduce employee attrition by delivering personalized development guidance based on workforce analytics and skill profiling. Using SAS Viya and governed AI workflows, the solution matches employees with tailored learning opportunities while supporting transparent, scalable, and data-driven workforce planning.
This post demonstrates how Agentic AI and SAS Viya can modernize SME loan origination by combining OCR, LLMs, governed decisioning, and interactive dashboards to accelerate transparent, explainable, and scalable credit decisions.
Learn how an AI voice agent built with SAS Viya and LLMs can transform fraud detection into real-time, automated fraud resolution through customer interaction and governed decisioning.
Shahrzad Azizzadeh and team discuss optimizing inspector assignments using SAS Optimization in federal and state meat processing facilities.
Demonstrates how network analytics can transform a simple link list into actionable insights for public health decision-making.
As AI agents act autonomously in public spaces, recent incidents highlight the urgent need for strong guardrails, ethical alignment, and human judgment to ensure AI augments society rather than undermines trust, work, and human connection.
As AI agents optimize how they communicate, the shift away from human-readable language underscores why transparency and interpretability are essential for building trust in autonomous systems.
