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A Unified Framework for Agentic Artificial Intelligence Enterprise Cloud Security API Modernization and Intelligent Data Integration
Full Stack Developer, Paris, France
Abstract
This paper presents a unified architectural framework for Agentic Artificial Intelligence (AI) to modernise Enterprise Cloud Security Application Programming Interfaces (APIs) and achieve intelligent data integration. Modern enterprise cloud environments are increasingly fragmented across multi-cloud structures, leading to operational siloing, latency in threat response, and data integration bottlenecks. Traditional security frameworks and static automation workflows struggle to adapt dynamically to evolving security vectors and heterogeneous data streams. To overcome these challenges, our proposed framework deploys autonomous, multi-agent AI networks capable of real-time reasoning, dynamic schema alignment, and continuous API security monitoring. The framework operates through four core layers: an orchestration tier, a semantic API translation pipeline, a zero-trust policy engine, and a distributed data synchronization bus. Agentic units continuously audit API endpoints, enforce zero-trust access controls, automatically remediate vulnerabilities, and orchestrate complex ETL (Extract, Transform, Load) pipelines using semantic context rather than hardcoded logic. Experimental evaluations demonstrate a 68% reduction in cross-cloud data integration latency, a 92% increase in automated threat remediation speed, and a significant improvement in API governance compliance across multi-cloud deployments. By bridging the gap between dynamic agentic decision-making and rigid enterprise cloud infrastructure, this research establishes a scalable foundation for next-generation, self-healing cloud ecosystems.
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 9 |
| Number | 5 |
| Pages | 17549-17557 |
| Published | 2025-10-13 |
| Issue | Vol. 9 No. 5 (2025): International Research Journal of Innovative Engineering (IRJIE) |
References
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27. Chukkala, R. (2025, April). The Convergence of CCAI, Chatbots, and RCS Messaging: Redefining Business Communication in the AI Era. In International Conference of Global Innovations and Solutions (pp. 194-213). Cham: Springer Nature Switzerland.
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30. Narayanan, S. (2023). Operationalizing artificial intelligence security in the cloud: A practical integration framework for enterprise risk management. International Journal of Future Innovative Science and Technology (IJFIST), 6(3), 10619.
31. Polamreddy, V. R. (2025). Reliable enterprise data exchange through event-driven synchronization and incremental processing. International Journal of Computer Technology and Electronics Communication, 8(3), 10776–10780.
32. Umasankar, P., & Saravanan, K. (2016). Artificial Neural Network based Smart Charging Systems for Lead Acid Batteries. Asian Journal of Research in Social Sciences and Humanities, 6(cs1), 181-191.
33. Juvvadi, R. R. (2018). Robotic process automation (RPA) in accounting: Measuring ROI and workforce displacement. International Journal of Research and Applied Innovations (IJRAI), 1(1), 17-21.
34. Meesala, L. K. (2024). Agentic AI in cybersecurity: Dual-use dynamics, threat vectors, and governance imperatives. World Journal of Advanced Research and Reviews, 24(3), 3667-3672.
2. Potdar, A., Gottipalli, D., Ashirova, A., Kodela, V., Donkina, S., & Begaliev, A. (2025, July). MFO-AIChain: An Intelligent Optimization and Blockchain-Backed Architecture for Resilient and Real-Time Healthcare IoT Communication. In 2025 International Conference on Innovations in Intelligent Systems: Advancements in Computing, Communication, and Cybersecurity (ISAC3) (pp. 1-6). IEEE.
3. Vayyasi, N. K. (2020). Decoding token volatility patterns with generative models deployed on cloud-native Java environments. International Journal of Engineering & Extended Technologies Research (IJEETR), 2(4), 1552-1565.
4. Chaganti, S. (2022). An AI-driven spatiotemporal crowd orchestration platform for large-scale theme parks: Hybrid machine learning, behavioural modelling, and real-time decisioning for safe and efficient guest flow. International Journal of Research and Applied Innovations, 5(6), 8231-8234.
5. Sudhan, S. K. H. H., & Kumar, S. S. (2015). An innovative proposal for secure cloud authentication using encrypted biometric authentication scheme. Indian journal of science and technology, 8(35), 1-5.
6. Gopisetty, S. (2024). What the Jenkins Logs Won’t Tell You: Using an AI Agent to Capture the Lost ‘Bank Memory’Behind a 76% Sprint Velocity Gain and Whether Another Community Bank Can Borrow It Without the Original Team. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(3), 259-276.
7. Kumar Adabala, P. (2021). Optimizing ERP Modernization: A Smart Data Migration Framework Approach. International Journal of Enhanced Research in Science, Technology &Amp, 61-72.
8. Mondal, K. K., Rahman, R., Bipasha, Y. A., & Kadir, A. (2023). Polygenic hazard score and amyloid PET imaging mediation analysis in Alzheimer's disease diagnosis. International Journal of Science and Research Archive, 10(2), 1451–1457. https://doi.org/10.30574/ijsra.2023.10.2.0980
9. Chaba, A. (2024). Unified Customer Identity and Profile Architecture for Customer Enterprise Orchestration. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(6), 9272-9285.
10. Wadhwa, R. (2023). Designing scalable enterprise systems using event-driven microservices and distributed data architecture for high-throughput business applications. International Journal of Computer Engineering and Technology, 14(3), 323-337.
11. Kale, P. (2024). A Multi-Agent AI Framework for Distributed DevOps Automation and Collaborative Decision-Making in Software Pipelines. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(1), 274-282.
12. Chettiyar, S. S. S. (2025). From Manual Email Tracking to AI-Driven Queues Enterprise Case Management Modernization. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(2), 9695-9704.
13. Gurram, S. K. (2025). Revolutionizing financial infrastructure: the convergence of blockchain and cloud in next-generation payment networks. Journal of Computer Science and Technology Studies, 7(4), 607-618.
14. Mohammed, S. (2022). Designing secure zero trust architectures for global enterprise environments. International Journal of Science, Research and Technology, 5(6), 8953-8956.
15. Challa, R. (2022). Optimizing InfiniBand Congestion Control for Large-Scale AI Model Training Workloads. International Journal of Engineering & Extended Technologies Research (IJEETR), 4(6), 5749-5757.
16. Chenna, S. (2025). Modernizing enterprise integration architecture: A case study of Oracle Cloud Integration. International Journal of Computer Technology and Electronics Communication, 8(3), 10768-10775.
17. Sarngadharan, S. (2025). Building a Resilient ODS Integrating Graph Algorithms and Azure for Enterprise Analytics. International Journal of Computer Technology and Electronics Communication, 8(2), 10433-10441.
18. Kesarpu, S. (2025). Zero-Trust Architecture in Java Microservices. International Journal of Networks and Security, 5(01), 202-214.
19. Gujarathi, M. (2023). Active-active data architecture for high-availability enterprise systems. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(1), 5976–5986.
20. Jayaraman, S., Rajendran, S., & P, S. P. (2019). Fuzzy c-means clustering and elliptic curve cryptography using privacy preserving in cloud. International Journal of Business Intelligence and Data Mining, 15(3), 273-287.
21. Meesala, A. (2023). A distributed Kafka-centric framework for high-throughput mid-price computation and intelligent time-series persistence in financial clouds. International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN, 2456-3307.
22. Venkiteela, P. (2025). Comparative analysis of leading API management platforms for enterprise API modernization. International Journal of Computer Applications, 187(54), 35-48.
23. Rajula, A. (2022). Cloud-based virtual patient engagement with intelligent scheduling and secure document management. International Journal of Future Innovative Science and Technology, 5(5), 9233–9245.
24. Sudhan, S. K. H. H., & Kumar, S. S. (2016). Gallant Use of Cloud by a Novel Framework of Encrypted Biometric Authentication and Multi Level Data Protection. Indian Journal of Science and Technology, 9, 44.
25. Vasa, M. R. (2024). Generative AI and Agentic Orchestration for Autonomous Data Engineering in Multi-Domain Enterprise Analytics Platforms. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(4), 364-369.
26. Sojol, J. I., Shihab, M. H., Ahamed, T., Siam, M. A. S., & Siddique, S. (2019, February). Nirob: a next generation green earth technology based innovative system for metropolitan sound pollution management. In 2019 21st international conference on advanced communication technology (ICACT) (pp. 722-727). IEEE.
27. Chukkala, R. (2025, April). The Convergence of CCAI, Chatbots, and RCS Messaging: Redefining Business Communication in the AI Era. In International Conference of Global Innovations and Solutions (pp. 194-213). Cham: Springer Nature Switzerland.
28. Anand, L., & Neelanarayanan, V. (2020, October). Enchanced multiclass intrusion detection using supervised learning methods. In AIP conference proceedings (Vol. 2282, No. 1, p. 020044). AIP Publishing LLC.
29. Anbazhagan, R. S. K. (2016). A Proficient Two Level Security Contrivances for Storing Data in Cloud.
30. Narayanan, S. (2023). Operationalizing artificial intelligence security in the cloud: A practical integration framework for enterprise risk management. International Journal of Future Innovative Science and Technology (IJFIST), 6(3), 10619.
31. Polamreddy, V. R. (2025). Reliable enterprise data exchange through event-driven synchronization and incremental processing. International Journal of Computer Technology and Electronics Communication, 8(3), 10776–10780.
32. Umasankar, P., & Saravanan, K. (2016). Artificial Neural Network based Smart Charging Systems for Lead Acid Batteries. Asian Journal of Research in Social Sciences and Humanities, 6(cs1), 181-191.
33. Juvvadi, R. R. (2018). Robotic process automation (RPA) in accounting: Measuring ROI and workforce displacement. International Journal of Research and Applied Innovations (IJRAI), 1(1), 17-21.
34. Meesala, L. K. (2024). Agentic AI in cybersecurity: Dual-use dynamics, threat vectors, and governance imperatives. World Journal of Advanced Research and Reviews, 24(3), 3667-3672.
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