Intelligent Enterprise Integration across Distributed Systems using AI for Cloud API Services and Real-Time Data Processing
DOI:
https://doi.org/10.21590/Keywords:
intelligent enterprise integration, distributed systems, artificial intelligence, cloud computing, API services, real-time data processing, machine learning, enterprise architecture, data analytics, interoperability, cloud APIs, intelligent automationAbstract
The increasing complexity of enterprise information environments has created a strong demand for intelligent integration across distributed systems. Organisations increasingly operate cloud applications, legacy platforms, microservices, databases, Internet of Things devices, and external services that continuously generate and exchange large volumes of data. Artificial intelligence (AI), cloud-based application programming interfaces (APIs), and real-time data processing provide important capabilities for integrating these heterogeneous environments while improving operational intelligence and responsiveness. AI can analyse complex datasets, automate decision-making, identify patterns, and support predictive business processes. Cloud API services provide standardised mechanisms for communication among distributed applications, enabling interoperability, scalability, and controlled access to enterprise resources. Real-time data processing allows organisations to analyse events as they occur rather than relying exclusively on historical batch processing. This paper examines the integration of distributed enterprise systems through AI-enabled cloud API services and real-time data processing. Particular attention is given to scalability, interoperability, security, data quality, latency, intelligent automation, and governance. The study argues that intelligent enterprise integration should be designed as a coordinated architecture in which APIs connect distributed services, cloud infrastructure provides elastic computational resources, AI transforms data into actionable intelligence, and real-time processing supports timely organisational responses. The integration of these capabilities can improve operational efficiency, customer experiences, predictive decision-making, and organisational agility while introducing challenges involving cybersecurity, system complexity, model reliability, data governance, and cloud dependency.
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