Deploy Insights - Quick Look
Accelerate model deployment with confidence. SAS Viya empowers you to operationalize analytics at scale—automating tasks, governing decisions, and deploying any model type with speed and transparency. From retraining to real-time monitoring, Viya helps you keep models performing and business outcomes on track.
Automate
Streamline manual tasks for feature engineering and model tuning.
Monitor
Continuously observe and assess model inputs, outputs and performance, utilizing built-in alerts.
Retrain
Revise, retrain or replace models, leveraging built-in pipelines to ensure optimal performance.
In SAS Viya, monitoring model performance was achieved with 8x more productivity than in competitive solutions, and retraining models was found to be 7x more productive. This efficiency provides MLOps teams with agility to quickly respond to any changes in model performance, ensuring high quality models are maintained.” The Futurum Group
Manage Models
With SAS Model Manager, take your model collection out of the lab and into production with the tools needed to execute fast model deployment and strong model governance. Easily embed models into operational systems and monitor their performance and health.
Unify assets
Track projects, models and supporting artifacts for simplified model management. Govern, organize and navigate modeling lineage and versioning for rapid, responsible access.
Track accuracy
Assess AI model accuracy, fairness and transparency using SAS model cards. With descriptive visuals, model cards are accessible to anyone involved in the analytics process – from data scientists to executives.
Validate and deploy
Easily test and validate model scoring logic using a no-code interface. Efficiently package and deploy models across environments – in-database, on-premises or in the cloud – without delay.
Monitor performance
Continuously monitor data, concept and model drift with built-in explainability, customizable to your needs. Alert stakeholders to model decay to minimize costly downtime.
Streamline MLOps
Maximize efficiency and reduce manual efforts with automated CI/CD pipelines. Standardize your modeling assets for repeatable, customizable automation and tailor alerts to keep the right people informed.
Build Decisions
SAS Intelligent Decisioning enables the development of decision flows and business rules using a drag-and-drop interface, with support for flexible programming languages for model deployments, decision trees, importing of LLMs, and agentic AI. It can be used to build both augmented and automated decision-making processes, offering exceptional scalability with the capability to handle over 7,000 real-time transactions per second.
Decisions at scale
Deliver, scale, test and govern trustworthy decisions in real time across the business and within your use cases.
Empower your team
With no-code, drag-and-drop UI, empower anyone in your organization to drive decisions, from business leaders to technical users.
Deploy models quickly
Accelerate time to market – and with support for SAS, open source or custom code from a single interface.
Integrated AI and ML
Improve your decision quality and increase competitive advantage from a common repository in your preferred language and with your LLMs.
Scale with SAS Container Runtime
Quickly execute with minimal effort on a compliant docker container for executing SAS or Python models and Python code in your choice of registry on Microsoft Azure, AWS and GCP.
The pressure to engage in data-driven decision making continues to rise with organizations having to make multiple types of decisions on a regular basis. The need to automate certain aspects of the decision-making process while sustaining control and monitor impact will drive the adoption of decision intelligence across certain business functions and industries." – Megha Kumar, Research Vice President, Analytics and AI, IDC
Streaming Analytics and Beyond
With SAS Event Stream Processing, operationalize your AI and extract actionable insights from streaming and batch data, from the edge to the cloud.
Batch and real-time insights
Address the full spectrum of data processing – from batch to high throughput continuous real-time events and everything in between – often combining sources to achieve outcomes.
Built-in analytics
Business users and developers can access the most comprehensive suite of built-in analytics for AI and machine learning, integrating advanced analytics, offline-trained models and third-party open source frameworks.
Real-time decisions
Process streaming data from a variety of sources to generate actionable intelligence with minimal latency. Respond promptly to changes, enhance operations and reduce risks.
Run and scale without limits
Deploy AI models seamlessly via containerization, whether in the cloud, on-premises or at the edge. Deliver scalable, distributed execution to meet your use case demands.
No other vendor comes close to SAS in offering advanced analytics that can be executed in real-time machine learning techniques." The Forrester Wave™ Streaming Data Platforms, Q4 2023
