Intelligent and Secure Enterprise Platforms: Converging AI Cloud Computing CRM Systems DevOps and Financial Technologies
Abstract
The rapid evolution of digital technologies has transformed the operational landscape of modern enterprises. Intelligent and secure enterprise platforms have emerged as integrated ecosystems that combine Artificial Intelligence (AI), Cloud Computing, Customer Relationship Management (CRM) systems, DevOps practices, and Financial Technologies (FinTech) to enhance organizational efficiency, innovation, and competitiveness. AI-driven analytics enable data-informed decision-making, predictive forecasting, and automation of routine processes. Cloud computing provides scalable infrastructure, flexible resource allocation, and cost-effective service delivery. CRM systems facilitate customer engagement, personalized experiences, and relationship management through centralized data platforms. DevOps methodologies improve software development and deployment cycles by promoting collaboration, continuous integration, and continuous delivery. FinTech solutions modernize financial operations through digital payments, blockchain technologies, risk analytics, and regulatory compliance mechanisms. The convergence of these technologies creates enterprise platforms capable of delivering intelligent automation, enhanced security, real-time business insights, and operational resilience. However, challenges such as cybersecurity threats, data privacy concerns, integration complexity, and regulatory compliance remain significant. This study explores the integration of AI, cloud computing, CRM systems, DevOps, and FinTech within enterprise environments, examines existing literature, proposes a research methodology for evaluating their effectiveness, and discusses the advantages and limitations associated with their adoption in contemporary organizations.Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 7 No. 6 (2024): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
13284-13291 |
Published |
December 18, 2024 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Bjarte Bogsnes (%2024). Intelligent and Secure Enterprise Platforms: Converging AI Cloud Computing CRM Systems DevOps and Financial Technologies. International Journal of Science, Research and Technology , Vol. 7 No. 6 (2024): International Journal of Science, Research and Technology (IJSRAT) , pp. 13284-13291. https://doi.org/10.15662/IJSRAT.2024.0706014 |
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4. Manda, P. (2022). Implementing hybrid cloud architectures with Oracle and AWS: Lessons from mission-critical database migrations. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7111–7122.
5. 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.
6. Navandar, P. (2022). Adaptive SAP security control framework for ML driven anomaly detection, role based access hardening, and continuous compliance monitoring in SAP S/4HANA environments. International Journal of Engineering & Extended Technologies Research (IJEETR), 4(3), 4939–4952. https://doi.org/10.15662/IJEETR.2022.0403005
7. Gollapudi, R. (2024). Event-aware multi-layer storage risk forecasting for Oracle database estates using HAPF. International Journal of Computational and Experimental Science and Engineering, 10(4). https://doi.org/10.22399/ijcesen.5183
8. Devineni, A. (2022). Proactive incident detection in multi-tenant financial cloud platforms. International Journal of Science, Research and Technology (IJSRAT), 5(4), 8136–8139.
9. Kotla, M. R. T. (2024). Intelligent automation in post-merger integration: Leveraging AI for entity matching, data mapping, and deduplication. International Journal of Computer Technology and Electronics Communication (IJCTEC), 7(3), 234–246.
10. Gajula, S. (2023). A Review of Anomaly Identification in Finance Frauds using Machine Learning System. International Journal of Current Engineering and Technology, 13(06).
11. Kavuri, S. (2022). Large Language Model (LLM)-Based Automation for Software Test Script Generation. Computer Fraud & Security, 17-28.
12. Shewale, V. (2024). Ransomware Resilience for Pipeline Operators. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(2), 7863-7868.
13. Parasa, M. (2023). A structured recruitment analytics framework for candidate screening and talent pool utilization in SAP SuccessFactors Recruiting. Global Journal of Engineering and Technology, 2(11), 29–39. https://gsarpublishers.com/gjet-vol-2-issue-11-november-2023/
14. Namdeo, A., Atulkar, A., & Porwal, R. K. (2022, August). Investigation of Two-Stage Epicyclic Gearbox for an Automobile for Energy Regeneration. In Biennial International Conference on Future Learning Aspects of Mechanical Engineering (pp. 363-376). Singapore: Springer Nature Singapore.
15. 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.
16. Juvvadi, R. R. (2023). Re-architecting intercompany accounting: An event-driven pattern for real-time matching and continuous elimination. International Journal of Applied Engineering & Technology, 5(S4), 414–424.
17. Boddupally, H. L. (2023). Automating Incident Triage and Root Cause Intelligence Through Large Language Model–Driven Correlation of System Logs and Operational Metrics in Large-Scale Distributed Environments. International Journal of Engineering & Extended Technologies Research (IJEETR), 5(6), 7676-7688.
18. Konakalla, K. (2023). Automating customer feedback collection in Salesforce Service Cloud for enhanced case management and service improvement. Journal of Marketing & Supply Chain Management, 1-3.
19. Goel, N. (2023). Zero Trust Architecture: A Revolutionary Approach to Cybersecurity. Res Militaris, Volume 13, Issue 3, pp. 6931–6940
20. Subramanyam, S. P. (2023). Secure identity and access management frameworks for cloud native DevOps systems. International Journal of Computer Technology and Electronics Communication, 6(4), 7357–7366.
21. Polamreddy, V. R. (2021). Engineering Reversible Enterprise Data Migrations: A Phased Rollout Framework for Financially Critical Retail Platforms. International Journal of Computer Technology and Electronics Communication, 4(2), 3414-3427.
22. Dama, H. B. (2024). Cross-Cloud Data Consistency Models for Always-On Banking Platforms. International Journal of Engineering & Extended Technologies Research (IJEETR), 6(4), 8468-8476.