A Cloud-Native and AI-Driven Architecture for Inclusive Digital Public Services with Broadband Connectivity Enterprise MLOps and SAP Platforms
DOI:
https://doi.org/10.15680/IJCTECE.2024.0705007Keywords:
Cloud-native architecture, inclusive digital services, artificial intelligence, broadband connectivity, enterprise MLOps, SAP platforms, public sector transformation, generative AI, digital inclusion, data governanceAbstract
Inclusive digital public services are essential for reducing socio-economic disparities and improving access to government and civic services. However, fragmented infrastructure, limited broadband connectivity, and the lack of scalable analytics platforms often hinder equitable service delivery. This paper proposes a cloud-native and AI-driven architecture that integrates broadband connectivity, enterprise MLOps, and SAP platforms to enable inclusive, scalable, and intelligent digital public services.
The proposed architecture leverages cloud-native microservices, broadband-enabled access networks, and SAP S/4HANA with SAP Business Technology Platform (BTP) as the digital core. Artificial intelligence components, including machine learning and Generative AI, are operationalized through enterprise MLOps pipelines to support real-time analytics, service personalization, demand forecasting, and citizen engagement. Broadband connectivity ensures low-latency, high-availability access across urban and rural environments, enabling digital inclusion at scale.
SAP platforms provide secure data governance, interoperability, and compliance, while cloud-native services ensure elasticity and resilience. The architecture incorporates identity management, data privacy controls, and explainable AI to align with public sector regulations and ethical AI principles. By unifying broadband infrastructure, AI-driven analytics, and SAP-based enterprise systems, the framework supports efficient service delivery, improved policy decision-making, and enhanced citizen experience.
This research demonstrates that cloud-native AI architectures, combined with enterprise MLOps and SAP platforms, can significantly improve inclusivity, operational efficiency, and transparency in digital public services. The proposed approach offers a scalable and sustainable foundation for governments and public institutions seeking to modernize service delivery while ensuring equitable access and regulatory compliance.
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