AI Powered Enterprise Integration Framework Using API First Architecture SAP and Multi Cloud Computing

Authors

  • Vignesh Dhanabal Software Developer, Tata Consultancy Services, Greater Toronto Area, Canada Author

DOI:

https://doi.org/10.15662/IJEETR.2026.0803013

Keywords:

Artificial Intelligence, API-First Architecture, SAP S/4HANA, SAP Business Technology Platform, Multi-Cloud Computing, Enterprise Integration, Cloud-Native Computing, Intelligent Automation, Predictive Analytics, DevSecOps, MLOps, Enterprise Digital Transformation

Abstract

The rapid evolution of enterprise digital transformation has significantly increased the demand for scalable, intelligent, and interoperable business integration platforms. Organizations are increasingly adopting Artificial Intelligence (AI), API-First Architecture, SAP enterprise solutions, and Multi-Cloud Computing to modernize legacy systems, improve business agility, and accelerate intelligent decision-making. However, traditional enterprise integration models often suffer from fragmented system connectivity, limited scalability, security vulnerabilities, and inefficient data exchange across heterogeneous enterprise environments. This paper proposes an AI Powered Enterprise Integration Framework that combines API-First Architecture, SAP S/4HANA, SAP Business Technology Platform (SAP BTP), Artificial Intelligence, intelligent automation, and Multi-Cloud Computing into a unified enterprise ecosystem. The proposed framework enables seamless communication between enterprise applications through standardized APIs while leveraging AI-driven analytics, predictive intelligence, intelligent workflow automation, and cloud-native technologies to optimize enterprise operations. Multi-cloud deployment enhances system availability, workload distribution, disaster recovery, and operational resilience across public and private cloud infrastructures. Furthermore, integrated API governance, Zero Trust Security, DevSecOps, MLOps, and enterprise monitoring strengthen cybersecurity and regulatory compliance. The framework supports real-time enterprise analytics, intelligent business process automation, adaptive resource management, and secure interoperability among distributed enterprise services. The proposed architecture provides organizations with a scalable, flexible, and intelligent integration platform that improves operational efficiency, reduces infrastructure complexity, enhances decision-making, and accelerates sustainable digital transformation across finance, manufacturing, healthcare, retail, logistics, telecommunications, and public-sector enterprises.

References

1. Joyce, S. (2024). Automated enterprise system reliability: Integrating AI-driven monitoring with cloud-based SAP deployment pipelines. International Journal of Research and Applied Innovations, 7(2), 10474-10482.

2. Suddala, V. R. A. K. (2025). Healthcare e-commerce platforms driving secure, scalable, and auditable service delivery. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(1), 9340–9351.

3. Chaganti, S. (2025). The "Aegis" Framework: A Multi-Cloud, Fault-Tolerant MLOps Architecture for Real-Time Financial Decisioning and Regulatory Compliance. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(6), 11113-11121.

4. Alam, M. M., Khan, M. I., & Sayem, S. M. (2026). Hybrid Cybersecurity: AI Models for Predicting Threats Across Multi-Cloud for US Business Environment. Frontiers in Computer Science and Artificial Intelligence, 5(9), 59-66.

5. Pothuri, M. K. (2025). Next-Gen Business Intelligence in Financial Services-Transforming Financial Efficiency with AI-Driven BI, Integration of AI/ML with BI tools. IJSAT-International Journal on Science and Technology, 16(4).

6. Syed, S. (2024). A zero-defect high sea sale automation framework for real-time ownership transfer and compliance in maritime trade systems. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7878–7891. https://doi.org/10.15662/IJEETR.2024.0602012

7. Devineni, A. (2022). Proactive incident detection in multi-tenant financial cloud platforms. International Journal of Science, Research and Technology (IJSRAT), 5(4), 8136–8139.

8. Mannem, S. (2024). From requirements to production: Managing cross-regional API deployments at Capital One. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7892–7898. https://doi.org/10.15662/IJEETR.2024.0602013

9. Rajan, P. K. (2026, February). Privacy-Preserving On-Device AI for Personalized Mobile Video Advertising. In SoutheastCon 2026 (pp. 1-6). IEEE.

10. Gandikota, S. P. (2024). Scaling national wireless services: A technical case study of T-Mobile's middleware evolution on AWS cloud. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7869–7877. https://doi.org/10.15662/IJEETR.2024.0602011

11. Manda, P. (2024). The role of machine learning in automating complex database migration workflows. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(3), 10451–10459.

12. Kale, P. (2025). Architecting Autonomous Testing Pipelines for Cloud-Native Systems Using AI-Driven Fault Injection and Predictive Analytics. International Journal of AI, BigData, Computational and Management Studies, 6(1), 207-216.

13. Navandar, P. (2023). Ensemble based intrusion detection in heterogeneous networks: A machine learning framework with zero trust integration. International Journal of Advanced Engineering Science and Information Technology, 6(1), 10827–10837. https://doi.org/10.15662/IJAESIT.2023.0601004

14. Grandhe, K. (2026, February). Explainable AI for Predicting SME Loan Defaults Using XGBoost and SHAP. In SoutheastCon 2026 (pp. 1-7). IEEE.

15. Anbazhagan, K. (2024). Trustworthy and Adaptive AI Systems for Enterprise Analytics Cybersecurity and Decision Optimization Using API-First and Cloud-Native Architectures. International Journal of Technology, Management and Humanities, 10(03), 65-74.

16. Gowda, M. K. S. (2024). Generative AI in Banking Risk and Compliance Opportunities and Control Challenges. International Journal of Future Innovative Science and Technology (IJFIST), 7(6), 13946.

17. Veershetty, G. (2024). Secure conversational AI: A unified enterprise architecture framework for integrating WhatsApp Business with global ERP systems. International Journal of Science, Research and Technology (IJSRAT), 7(1), 11360–11372.

18. Chettiyar, S. S. S. (2024). Agentic AI orchestrated conversational payment pipelines with drift-aware transaction. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(3), 8166–8174. https://doi.org/10.15662/IJEETR.2024.0603008

19. Lanka, S. (2024). Redefining Digital Banking: ANZ’s Pioneering Expansion into Multi-Wallet Ecosystems. International Journal of Technology, Management and Humanities, 10(01), 33-41.

20. Juvvadi, R. R. (2022). Machine learning for anomaly detection in the financial close: A journal entry risk-scoring framework for SAP S/4HANA. International Journal of Communication Networks and Information Security, 14(3), 1684–1695.

21. Panda, S. S. (2025). Redefining cloud-native performance: A technical evaluation of Microsoft Azure’s Cobalt 100 ARM-based virtual machines. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(2), 11815–11830.

22. Govindan, V. (2023). AI-powered optimization of non-production environments: Turning constraints into business value. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(1), 8089–8104. https://doi.org/10.15662/IJRPETM.2023.0601009

23. Damarched, M. K. (2025). Data Governance Challenges in ITSM Platform Transitions. International Journal of Computer Technology and Electronics Communication, 8(6), 11881-11890.

24. Kotla, M. R. T. (2025). Enterprise integration lessons from four digital frontlines: A comparative analysis of modern IT ecosystems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(3), 32-42.

25. Sarngadharan, S. (2024). A secure, zero-trust mobile expert locator for global professional services firms. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(3), 8157–8165. https://doi.org/10.15662/IJEETR.2024.0603007

26. Sunnam, S. V. B. R. (2023). AI and machine learning architectures for autonomous reliability in financial data platforms. Computer Fraud and Security, 2023(7), 53–61.

27. Barigidad, S., Hameed, S., Karri, N., Jangam, S. K., Pedda, P. S. R., & Gupta, D. (2025, December). Computational Modeling of AI-Enhanced Learning Pathways: A Mathematical Framework for Optimizing Knowledge Acquisition, Cognitive Load Management, and Student Performance in STEM Education. In 2025 International Conference on AI-Driven STEM Education and Learning Technologies (AISTEMEDU) (pp. 1-7). IEEE.

28. Indurthy, V. S. K. (2025). ETL-Driven Data Integration for Enhanced Pharmaceutical Manufacturer Rebate Processing. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 8(1), 11606-11615.

29. Sivakumer, D. (2023). ServiceNow-based project management models for scalable enterprise workflow automation. International Journal of Future Innovative Science and Technology (IJFIST), 6(4), 11003–11014. https://doi.org/10.15662/IJFIST.2023.0604006

30. 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. https://doi.org/10.15680/IJCTECE.2025.0803012

31. Polamreddy, V. R. (2024). Hybrid On-Premise to Cloud Data Migration: Architectural Patterns for Controlled One-Way Synchronization. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(3), 8143-8156.

32. Nagarajan, G., & Mali, R. K. (2024). Cloud-Integrated AI Models for Enhanced Financial Compliance and Audit Automation in SAP with Secure Firewall Protection. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 7(1), 9692-9699.

33. Makkena, B. (2023). PromptOps: Building prompt-driven DevOps workflows for infrastructure-as-code automation. International Journal of Communication Networks and Information Security, 15(10), 12–30.

34. Anumula, S. K. (2025). A Novel Process Framework for Manufacturing Supplier Collaboration in Original Equipment Manufacturing (OEM). European Journal of Logistics, Purchasing and Supply Chain Management, 13(1), 75-92.

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Published

2026-05-28

How to Cite

AI Powered Enterprise Integration Framework Using API First Architecture SAP and Multi Cloud Computing. (2026). International Journal of Engineering & Extended Technologies Research (IJEETR), 8(3), 5120-5139. https://doi.org/10.15662/IJEETR.2026.0803013