A Trust Architecture for Enterprise Decision Automation
Keywords:
Governed Agentic AI,Enterprise Service Automation,Secure Knowledge Management,Knowledge-Centric Decision Intelligence,AI Agents,Retrieval-Augmented Generation (RAG),Enterprise Knowledge Graphs,Intelligent Workflow Orchestration,AI Governance and Compliance,Context-Aware Decision Support.Abstract
In fast-changing environments, enterprises must adapt quickly to survive. One increasingly common strategy is to automate parts of an organization by delegating business functions to intelligent agents—software systems capable of performing work autonomously. This paper describes an architecture in which such agents operate around a central execution orchestrator and decision workflows. However, a key limitation of current agentic systems is that decision-making speed—critical for throughput and reliability—is often insufficient, resulting in operational delays.
This limitation stems primarily from a gap in the underlying architecture. In enterprise settings, it is essential that the internal reasoning processes of agent-based decision-makers be coordinated through an orchestrator, and that the decision pipeline supporting this reasoning operate with adequate speed. This orchestration layer forms the core of secure, knowledge-centric decision-making: the generation of decisions, recommendations, and predictions that meet the quality and assurance standards required by the task domain. Secure knowledge-centric reasoning thus serves as a necessary counterpart to the agentic foundation being automated—enabling the speed, reliability, and trust required for decisions that directly affect business function execution.
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Copyright (c) 2025 Vikram Boga (Author)
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