TLDR: SAS, a leader in data and AI, has launched its new Retrieval Agent Manager (RAM) designed to significantly boost business productivity by transforming unstructured enterprise data into actionable insights. Built on the retrieval augmented generation (RAG) framework, RAM offers a no-code solution to deliver fast, accurate, and context-aware AI responses, addressing key challenges in leveraging generative AI for informed decision-making.
CARY, N.C. – September 25, 2025 – SAS, a prominent player in the data and artificial intelligence landscape, today announced the release of its innovative SAS Retrieval Agent Manager (RAM). This new offering is poised to revolutionize how enterprises harness the power of generative and agentic AI, particularly in dealing with the vast and growing volume of unstructured data.
The challenge of unlocking value from unstructured data, such as text and images, has long been a significant hurdle for businesses. With over 80% of enterprise data existing in these formats and growing at an astounding rate of 50% to 60% annually, traditional generative AI approaches have often proven to be code-heavy, complex, and inefficient, failing to yield consistent and compelling results. SAS RAM directly confronts these issues.
SAS Retrieval Agent Manager streamlines the intricate process of converting raw, unstructured data from a company’s knowledge base into precise and relevant answers, thereby facilitating superior business decisions. The platform is engineered to tackle fundamental challenges across all industries, enabling organizations to integrate AI seamlessly and reliably into their existing systems.
“SAS Retrieval Agent Manager transforms fragmented, unstructured information into actionable enterprise knowledge, to make more informed decisions faster,” stated Kathy Lange, Research Director for the AI and Automation practice at analyst firm IDC. Lange further highlighted that “By leveraging generative and agentic AI, RAM provides a user-friendly interface to build and modernize organizational processes without overhauling existing systems.”
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Built upon the robust retrieval augmented generation (RAG) framework, RAM stands out as a no-code solution. This design allows it to deliver rapid, accurate, and context-aware AI responses directly from an organization’s unstructured content, promising to supercharge business productivity and decision-making capabilities.
