Cloud Native Generative AI Platforms for Personalized Mobile Engagement and Intelligent Enterprise Integration
DOI:
https://doi.org/10.15662/IJEETR.2026.0801006Keywords:
Cloud-native AI, generative AI platforms, personalized mobile engagement, large language models, mobile personalization, enterprise integration, microservices, Kubernetes, serverless computing, API-driven architecture, event-driven systems, real-time analytics, MLOps, customer data platforms, intelligent automation, scalable infrastructureAbstract
Cloud-native generative AI platforms are transforming personalized mobile engagement and intelligent enterprise integration by combining scalable infrastructure with context-aware AI capabilities. Built on microservices, Kubernetes orchestration, serverless computing, and API-driven architectures, these platforms enable dynamic content generation, conversational interfaces, recommendation engines, and adaptive user experiences across mobile applications. By leveraging large language models (LLMs), real-time analytics, and customer data platforms, organizations can deliver hyper-personalized interactions that evolve based on user behavior, preferences, and contextual signals.
At the enterprise level, cloud-native integration frameworks facilitate seamless connectivity between generative AI services, backend systems, CRM platforms, and data lakes. Event-driven architectures and streaming pipelines ensure low-latency data exchange, while AI-powered automation enhances decision-making, campaign optimization, and operational efficiency. Secure model deployment, observability, governance controls, and MLOps pipelines maintain reliability and compliance at scale. Together, these capabilities establish intelligent, scalable ecosystems that drive customer engagement, digital innovation, and enterprise agility in a rapidly evolving mobile-first landscape
References
1. Ponugoti, M. (2024). AI-driven microservice architectures: Enhancing compliance and decision intelligence in cloud environments. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 7(5), 14869–14880.
2. Natta, P. K. (2025). Architecting autonomous enterprise platforms for scalable, self-regulating digital systems. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 8(5), 17292–17302. https://doi.org/10.15662/IJAESIT.2025.0805002
3. Bathina, S. (2025). Composable commerce architectures: Building agile retail systems. International Journal of Advanced Research in Computer Science & Technology (IJARCST), 8(3), 12226–12231.
4. Mudunuri, P. R. (2025). Socio-technical impacts of automation in regulated scientific organizations. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 8(3), 16488–16498.
5. Chintalapudi, S. (2025). From backend to business: Fullstack architectures for self-serve RAG and LLM workflows. International Journal of Research Publications in Engineering Technology and Management (IJRPETM), 8(3), 12121–12132.
6. Gurajapu, A., & Garimella, V. (2025). Serverless vs. containerized workloads: Comparative performance and cost under bursty telecom traffic. International Journal of Computer Technology and Electronics Communication (IJCTECE), 8(1), 10085–10088.
7. Devi, C., Inampudi, R. K., & Vijayaboopathy, V. (2025). Federated data-mesh quality scoring with Great Expectations and Apache Atlas lineage. Journal of Knowledge Learning and Science Technology, 4(2), 92–101.
8. Rajasekharan, R. (2025). Automation and DevOps in database management: Advancing efficiency reliability and innovation in modern data ecosystems. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(4), 10284–10292.
9. Panchakarla, S. K. (2025). Personalized mobile engagement in global hospitality: A unified framework for guest communication compliance. Journal of Computational Analysis and Applications, 34(7).
10. Surisetty, L. S. (2025). AI-driven compliance: Using data science to ensure fair pricing and policy alignment in healthcare systems. International Journal of Computer Technology and Electronics Communication, 8(1), 10069–10084.
11. Kamadi, S. (2024). GenAI data engineering: Synthetic data and feature engineering framework for cloud analytics. World Journal of Advanced Research and Reviews, 24(1), 2867–2877.
12. Jeyaraman, J., Keezhadath, A. A., & Ramalingam, S. (2025). AI-Augmented Quality Inspection in Aerospace Composite Material Manufacturing. Essex Journal of AI Ethics and Responsible Innovation, 5, 1-32.
13. Gaddapuri, N. S. (2021). Big data storage observation system. Power System Protection and Control, 49(2), 7–19.
14. Gangina, P. (2025). The role of cloud architecture in shaping a sustainable technology future. International Journal of Research Publications in Engineering Technology and Management (IJRPETM), 8(5), 12827–12833.
15. Sriramoju, S. (2025). Architecting scalable API-led integrations between CRM and ERP platforms in financial enterprises. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(4), 10303–10311.
16. Ferdousi, J., Shokran, M., & Islam, M. S. (2026). Designing Human–AI Collaborative Decision Analytics Frameworks to Enhance Managerial Judgment and Organizational Performance. Journal of Business and Management Studies, 8(1), 01-19.
17. Mulla, F.A.: Building scalable mobile applications: a comprehensive guide to shared component architecture. SSRN Electron. J. (2025). https://doi.org/10.2139/ssrn.5054866
18. Thakran, V. (2025, June). An Analysis of Machine Learning Solutions for Precise Forecasting of Oil and Gas Pipeline. In 2025 International Conference on Intelligent Computing and Knowledge Extraction (ICICKE) (pp. 1-6). IEEE.
19. Navandar, P. (2025). AI Based Cybersecurity for Internet of Things Networks via Self-Attention Deep Learning and Metaheuristic Algorithms. International Journal of Research and Applied Innovations, 8(3), 13053-13077.
20. Chennamsetty, C. S. (2025). Bridging design and development: Building a generative AI platform for automated code generation. International Journal of Computer Technology and Electronics Communication, 8(2), 10420–10432.
