Architecting Cognitive Computing Frameworks for Real-Time Decision Support in Enterprise Environments
Keywords:
Cognitive Computing, Real-Time Decision Support, Enterprise Systems, AI Frameworks, Intelligent Automation, Data-Driven Decision-MakingAbstract
In modern enterprise ecosystems, real-time decision-making is a strategic imperative driven by increasingly complex and dynamic operational contexts. Cognitive computing—rooted in AI, machine learning, and natural language processing—offers transformative potential to augment decision support systems. This paper explores a structured framework for integrating cognitive computing within enterprise infrastructures, enabling intelligent automation, contextual data interpretation, and adaptive response capabilities. The proposed architecture facilitates data ingestion, real-time analytics, and decision orchestration through hybrid cloud-edge deployment models. A synthesis of prior research reveals essential design principles, including modularity, explainability, and scalability, which are crucial for effective implementation.
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