Real-Time AI: Building Intelligent Stream Processing Pipelines

Himanshu Adhwaryu

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 1, 3042-3050

Abstract: This comprehensive technical article explores the evolution and implementation of real-time AI systems through stream processing pipelines. It explores the transformation from traditional batch processing to dynamic, real-time intelligence, highlighting the architectural components, implementation patterns, and industry applications. The article discusses critical aspects of stream processing foundations, AI/ML integration layers, and real-time inference engines while addressing challenges in feature engineering, model deployment, and system monitoring. Through detailed analysis of applications across financial services, healthcare, and insurance sectors, the article demonstrates how organizations leverage real-time AI to achieve significant improvements in operational efficiency, decision-making capabilities, and customer service delivery. The article also explores emerging trends, including edge computing integration, federated learning, and quantum computing applications, providing insights into the future direction of real-time AI systems.

Keywords: Artificial Intelligence; Machine Learning; Real-time Processing; Stream Computing; System Architecture (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112313
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i1:id:978

DOI: 10.32628/CSEIT251112313

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