What is SAS Retrieval Agent Manager?
SAS Retrieval Agent Manager enables fast, accurate and context-aware GenAI responses from unstructured enterprise data. Built on the Retrieval Augmented Generation (RAG) framework, it simplifies a traditionally complex architecture, allowing you to scale AI adoption without compromising flexibility or precision. Quickly unlock enterprise knowledge, reduce manual data extraction and overcome the common limitations of standard RAG implementations.
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Accelerate time to value & make faster decisions
Our no-code interface with optimized AI performance delivers precise, context-rich answers. Chatbots and virtual assistants using RAG improve response relevance, leading to a 35% boost in customer satisfaction.
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Enhance trust in AI outcomes with verified grounding, human oversight & built-in evaluation
Improve content accuracy by up to 40% compared with traditional AI models, reduce SME escalations and ensure transparency with citation-backed responses, human oversight, and robust security and governance.
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Scale efficiently & cost-effectively with flexible AI
Efficiently scale AI across use cases with flexible integrations and plug-and-play LLMs and databases, avoiding vendor lock-in and supporting broad data compatibility. Support for multiple LLMs, vector database and API integrations reduces integration efforts without re-architecture.
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Automate decisions with autonomous agents
Automate complex workflows with intelligent, goal-driven agents that seamlessly integrate and collaborate to boost productivity, reducing research time by 50% in enterprise applications.
Key features
Empowering you to unlock knowledge value securely and efficiently.
Intuitive no-code experience
Empowers nontechnical users with a no-code interface to build and manage workflows, with support for diverse document types, multilingual OCR and usage monitoring.
Trustworthy & transparent AI
Delivers citation-backed, source-grounded responses with built-in evaluation and human-in-the-loop oversight to ensure transparency, traceability and trust
Modular, plug-and-play architecture
Supports multiple third-party LLMs and vector databases with no vendor lock-in, and includes native integration with file systems and Git for seamless enterprise onboarding.
High-performance & enterprise-ready integration
Delivers fast, efficient AI through model acceleration techniques and offers seamless integration into enterprise systems via robust APIs and secure, scalable deployment.
Model context protocol (MCP)
Empowers agents to go beyond retrieval, orchestrate APIs and automate enterprise processes with schema-driven, auditable and reusable tool calls.
Autonomous agent orchestration
Supports orchestration of agents that retrieve, reason and act across systems – automating complex, high-value agentic AI workflows with precision, integration and parallel execution.
Flexible deployment options
Provides robust support for on-premises deployments, giving you full control over your data with easy extension to cloud or hybrid environments.
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SAS Retrieval Agent Manager frequently asked questions
What is SAS Retrieval Agent Manager?
SAS Retrieval Agent Manager is a no-code platform that delivers context-aware AI responses from unstructured enterprise data using a Retrieval Augmented Generation (RAG) framework.
What does SAS Retrieval Agent Manager do?
SAS Retrieval Agent Manager ingests and processes unstructured documents – text, images, PDFs – and enables chatbots or AI agents to return precise, citation-backed answers or actions, reducing manual data extraction.
What are the main benefits of using SAS Retrieval Agent Manager?
SAS Retrieval Agent Manager:
- Speeds up decision making with fast, context-rich outputs.
- Improves answer accuracy with grounded, transparent responses.
- Scales across large, growing data volumes without vendor lock-in.
Who uses SAS Retrieval Agent Manager?
SAS Retrieval Agent Manager is used by enterprises across industries – e.g., banking, insurance, manufacturing, health care, public sector – that need to unlock insights from unstructured data for compliance, customer service, claims, maintenance or regulatory workflows.
How does SAS Retrieval Agent Manager integrate with enterprise systems and AI?
SAS Retrieval Agent Manager offers a modular, plug-and-play architecture that allows integration with multiple LLMs, vector databases and enterprise data stores – via APIs or AI/chatbot interfaces – without requiring a major infrastructure overhaul.
Is SAS Retrieval Agent Manager suitable for large or regulated data environments?
Yes – it supports secure on-premises or hybrid deployment, governance, citation-backed responses and human-in-the-loop oversight to maintain auditability and compliance.
What kind of workflows can SAS Retrieval Agent Manager support?
SAS Retrieval Agent Manager supports a variety of AI-powered workflows, from simple Q&A chatbots to fully autonomous agents that retrieve data, reason over it and trigger actions – useful for fraud detection, claims processing, policy retrieval, maintenance instructions and more.