SAS, a data and AI company, has introduced SAS Decision Builder, a cloud-based intelligent decision-making tool now available in private preview on Microsoft Fabric. Leveraging SAS's advanced decision-making capabilities, this solution integrates multiple AI models, rules, and logic into a cohesive workflow, helping customers make more efficient, secure decisions.
"By deeply integrating aspects of our intelligent decisioning solution into Microsoft Fabric, we're delivering a cohesive experience for customers where they can utilize key capabilities like Power Automate Workspaces, OneLake for reporting or other tools in concert with SAS Decision Builder to complete their decisioning lifecycles. We're making it faster and easier for customers to connect across shared workspaces and deliver decisions that generate real results," said Shadi Shahin, Vice President of Product Strategy at SAS.
SAS Decision Builder streamlines the analytics life cycle, allowing users to design, integrate, and deploy models and decisions. This is beneficial for organizations aiming to enhance their analytics investments through AI-driven decision-making. Now part of Microsoft Fabric, SAS Decision Builder offers seamless access to data via Microsoft Fabric OneLake, enabling users to test, modify, and execute decisions within the Fabric environment, adapting swiftly to market changes and business requirements.
Enhanced user experience
With its native integration into Microsoft Fabric, SAS Decision Builder allows business analysts and domain experts to access and design decision flows through an intuitive low-code editor. This solution utilizes machine learning and LLMs to manage the entire decision-making lifecycle. Fabric’s machine learning features are seamlessly integrated, enabling users to leverage existing model-building pipelines for actionable insights. Additionally, SAS Decision Builder offers robust governance features, ensuring secure and transparent management of decision flows.
AI-Enhanced customer insights
The integration extends to Azure AI Services, incorporating generative AI elements like LLMs within decision flows. This combination of LLMs and predictive AI enables for comprehensive data analysis across various industries, streamlining scenario planning, outcome analysis, and personalized customer experiences.
For instance, in customer service, call center representatives can use AI-driven responses to better meet individual customer needs. Financial services can benefit as well; credit companies can generate real-time offers on multiple platforms, and lenders can streamline loan approval processes.Moreover, SAS Decision Builder can improve fraud detection and authorization procedures. IT professionals can utilize LLMs to develop tools that identify phishing attempts, bolster security, reduce data breaches, and ensure compliance in regulated sectors.
