Logicgate Technologies Inc., USA.
World Journal of Advanced Research and Reviews, 2025, 26(01), 2524-2533
Article DOI: 10.30574/wjarr.2025.26.1.1326
Received on 26 February 2025; revised on 16 April 2025; accepted on 18 April 2025
This article presents a comprehensive comparative analysis of AI-powered Integration Platform as a Service (iPaaS) solutions transforming enterprise integration landscapes. As organizations navigate increasingly complex digital ecosystems, these platforms leverage artificial intelligence to address traditional integration challenges through automated data mapping, intelligent error handling, predictive analytics, and natural language processing capabilities. The article examines leading market solutions, evaluating their distinctive strengths and limitations. Through a detailed financial services case study, the article demonstrates how organizations balance technical capabilities with business priorities when selecting integration platforms. Implementation considerations spanning organizational readiness, technical infrastructure, and strategic alignment are explored, highlighting critical success factors beyond technical functionality. It concludes by examining emerging trends that will shape future integration platforms, including autonomous integration capabilities, edge intelligence, and embedded business analytics, providing valuable insights for organizations seeking to leverage AI-enhanced integration to drive digital transformation.
AI-Powered Integration Platforms; Enterprise Application Connectivity; Machine Learning For Data Mapping; Autonomous Integration Workflows; Edge Computing Integration
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Tejaswi Bharadwaj Katta. Comparative analysis of AI-powered iPaaS Solutions for Enterprise Integration. World Journal of Advanced Research and Reviews, 2025, 26(01), 2524-2533. Article DOI: https://doi.org/10.30574/wjarr.2025.26.1.1326.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0