Intelligent Governed Enterprise Ecosystems Powered by AI Cloud Native Platforms and Secure Broadband Connectivity

Main Article Content

Gopalakrishna Karamchand

Abstract

In today’s rapidly evolving digital landscape, enterprises require intelligent, agile, and secure ecosystems to sustain competitive advantage. The integration of Artificial Intelligence (AI), cloud-native platforms, secure mobile architectures, and high-speed broadband connectivity enables organizations to streamline operations, enhance decision-making, and foster collaboration. AI-driven analytics and automation improve operational efficiency, while cloud-native platforms ensure scalability, resilience, and cost-effectiveness. Secure mobile architectures allow workforce mobility without compromising data privacy and compliance, and broadband connectivity facilitates real-time data exchange across distributed enterprise networks. This research explores the design principles, governance models, and technological frameworks necessary to build intelligent enterprise ecosystems that are adaptive, resilient, and secure. By reviewing existing literature, analyzing case studies, and proposing a methodological framework, the study identifies best practices and potential challenges in implementing such integrated solutions. The findings provide insights into achieving a balance between technological innovation, operational efficiency, and regulatory compliance, offering a roadmap for enterprises to navigate complex digital transformations. The study highlights the transformative potential of converging AI, cloud-native architectures, secure mobile solutions, and broadband connectivity to drive enterprise intelligence and governance in the modern business environment.

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How to Cite

Intelligent Governed Enterprise Ecosystems Powered by AI Cloud Native Platforms and Secure Broadband Connectivity. (2023). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(6), 9746-9754. https://doi.org/10.15662/IJRPETM.2023.0606018

References

1. Genne, S. (2023). A secure bridge-based execution architecture for hybrid mobile applications. International Journal of Research and Applied Innovations (IJRAI), 6(1), 8316–8328.

2. Surisetty, L. S. (2022). Designing Intelligent Integration Engines for Healthcare: From HL7 and X12 to FHIR and Beyond. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 5(1), 5989–5998.

3. Ramsugeerthi, A., Neela Madheswari, A., Umamaheswari, A., & Prassana, D. (2020). Location navigation assistance for educational institutions using augmented reality. Journal of Xidian University, 14(4), 1342–1347. https://doi.org/10.37896/jxu14.4/156

4. Navandar, P. (2022). SMART: Security Model Adversarial Risk-based Tool. International Journal of Research and Applied Innovations, 5(2), 6741–6752.

5. Anumula, S. R. (2023). Resilience engineering for intelligent enterprise platforms. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(1), 5954–5965.

6. Inbavalli, M., & Arasu, T. (2015). Efficient Analysis of Frequent Item Set Association Rule Mining Methods. International Journal of Scientific & Engineering Research, 6(4).

7. Hasenkhan, F., Mohammed, A. S., & Saminathan, M. (2021). Leveraging AI for Automated Customs Document Processing: A Case Study on AI-Powered Document Intelligence. American Journal of Data Science and Artificial Intelligence Innovations, 1, 69–102.

8. 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.

9. Lakshmi, A. J., Dasari, R., Chilukuri, M., Tirumani, Y., Praveena, H. D., & Kumar, A. P. (2023, May). Design and Implementation of a Smart Electric Fence Built on Solar with an Automatic Irrigation System. In 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 1553–1558). IEEE.

10. Anand, L., & Neelanarayanan, V. (2019). Liver disease classification using deep learning algorithm. BEIESP, 8(12), 5105–5111.

11. Kamadi, S. (2021). Risk Exception Management in Multi-Regulatory Environments: A Framework for Financial Services Utilizing Multi-Cloud Technologies.

12. Archana, R., & Anand, L. (2023, May). Effective Methods to Detect Liver Cancer Using CNN and Deep Learning Algorithms. In 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1–7). IEEE.

13. Keezhadath, A. A., Amarapalli, L., & Sethuraman, S. (2022). Scalable Data Lake Architectures for Multi-Industry Enterprise Analytics. Essex Journal of AI Ethics and Responsible Innovation, 2, 136–175.

14. Sabin Begum, R., & Sugumar, R. (2019). Novel entropy-based approach for cost-effective privacy preservation of intermediate datasets in cloud. Cluster Computing, 22(Suppl 4), 9581–9588.

15. Gaddapuri, N. S. (2022). APPLICATION OF QUANTUM COMPUTING IN DIGITAL EDUCATION SYSTEMS. Power System Protection and Control, 50(2), 12–24.

16. 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.

17. Gangina, P. (2023). Edge computing architectures for IoT data aggregation in industrial manufacturing. International Journal of Humanities and Information Technology (IJHIT), 5(1), 48–67. https://www.ijhit.info

18. Sethuraman, S., Devi, C., & Murthy, C. G. (2022). Policy-as-Code Row-Level Security: Compiling DPL Rules into Spark SQL Views. American Journal of Data Science and Artificial Intelligence Innovations, 2, 673–705.

19. Aashiq Banu, S., Sucharita, M. S., Soundarya, Y. L., Nithya, L., Dhivya, R., & Rengarajan, A. (2020). Robust Image Encryption in Transform Domain Using Duo Chaotic Maps—A Secure Communication. In Evolutionary Computing and Mobile Sustainable Networks: Proceedings of ICECMSN 2020 (pp. 271–281). Singapore: Springer Singapore.

20. Adepu, R. (2022). Ensuring High Availability and Disaster Recovery in Hybrid IT Environments: A Systems Architecture Approach. International Journal of Research and Applied Innovations, 5(2), 452-461.

21. Panyala, V. R. (2021). Designing fault-tolerant distributed systems for high-availability consumer internet platforms. International Journal of Research Publications in Engineering, Technology and Management, 4(6), 11–22.

22. Kunadi, S. K. (2022). Designing high-performance data pipelines using Snowflake and cloud-native architectures. International Journal of Research and Applied Innovations, 5(6), 8220-8230.

23. Kotla, M. R. T. (2023). Autonomous enterprise integration: The future of self-healing data and API ecosystems. International Journal of Research and Applied Innovations (IJRAI), 6(3), 5968–5971.

24. Katta, T. B. (2022). A Capability Maturity Framework for Event-Driven Integration: Benchmarking Kafka and Pulsar in Enterprise Environments. International Journal of Future Innovative Science and Technology (IJFIST), 5(6), 9589.

25. Kavuri, S. (2023). Machine learning approaches for security vulnerability detection in software testing. Computer Fraud & Security, 21-31.

26. Shewale, V. (2022). IT/OT Convergence: A Zero Trust Reference Architecture for the Energy Sector. International Journal of Science, Research and Technology, 5(5), 8494-8502.

27. Parasa, M. (2020). Control-mapped AI governance for high-risk HR decisions in SAP SuccessFactors: Audit-ready metrics for recruiting, performance calibration, and internal mobility. SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology, 12(2), 153–168. https://doi.org/10.18090/samriddhi.v12i02.15

28. Subramanyam, S. P. (2023). Cloud infrastructure automation and role-based access governance in Azure Kubernetes services. International Journal of Research Publications in Engineering, Technology and Management, 6(2), 8392–8400.

29. Namdeo, A. (2021). Quantum-accelerated cloud BI query optimization. International Journal of Engineering & Extended Technologies Research (IJEETR), 3(5), 3715–3724.

30. Adepu, G. (2021). Zero-Trust Digital Government Platforms: Secure Identity, API Governance, and Cloud-Native Service Architecture. International Journal of Engineering & Extended Technologies Research (IJEETR), 3(3), 3089-3093.

31. Sengupta, J. (2019). Automated Inception Network based Cardiac Image Segmentation Analysis. International Journal of Advanced Science and Technology, 28(20), 953-962

32. Ponugoti, M. (2023). Bridging the digital divide: Architecture for equitable technological access. International Journal of Computer Technology and Electronics Communication (IJCTEC), 6(3), 6991–7002.

33. Yashwanth, K., Adithya, N., Sivaraman, R., Janakiraman, S., & Rengarajan, A. (2021, July). Design and Development of Pipelined Computational Unit for High-Speed Processors. In 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1–5). IEEE.

34. Mudunuri, P. R. (2023). Automation-driven reliability engineering for public-sector biomedical systems. International Journal of Humanities and Information Technology (IJHIT), 5(1), 68–86.

35. Ananth, S., Kalpana, A. M., & Vijayarajeswari, R. (2020). A dynamic technique to enhance quality of service in software-defined network-based wireless sensor network (DTEQT) using machine learning. International Journal of Wavelets, Multiresolution and Information Processing, 18(01), 1941020.

36. Paul, D., Sudharsanam, S. R., & Surampudi, Y. (2021). Implementing Continuous Integration and Continuous Deployment Pipelines in Hybrid Cloud Environments: Challenges and Solutions. Journal of Science & Technology, 2(1), 275–318.

37. Ramidi, M. (2023). Implementing privacy-focused data sharing frameworks for mobile healthcare communication. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(3), 8746–8757.

38. Vimal Raja, G. (2021). Mining Customer Sentiments from Financial Feedback and Reviews using Data Mining Algorithms. International Journal of Innovative Research in Computer and Communication Engineering, 9(12), 14705–14710.

39. Pasumarthi, H. (2023). Applying machine learning to high-volume banking platforms: From transaction data to predictive risk intelligence. International Journal of Computer Technology and Electronics Communication, 6(4), 7352–7356

40. Adari, V. K. (2024). How Cloud Computing is Facilitating Interoperability in Banking and Finance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(6), 11465–11471.

41. Perla, S. (2022). Salesforce automation with Flows: From admin to AI. Journal of Computational Analysis and Applications, 30(1), 850–856. https://www.researchgate.net/profile/Srikanth-Perla-2/publication/391454730_Salesforce_Automation_with_Flows_From_Admin_to_AI/links/6818eb11bd3f1930dd6c866f/Salesforce-Automation-with-Flows-From-Admin-to-AI.pdf

42. Muthirevula, G. R., Kotapati, V. B. R., & Ponnoju, S. C. (2020). Contract Insightor: LLM-Generated Legal Briefs with Clause-Level Risk Scoring. European Journal of Quantum Computing and Intelligent Agents, 4, 1–31.

43. Gaddapuri, N. S. (2022). Application of Quantum Computing in Digital Education Systems. Power System Protection and Control, 50(2), 12–24.