AI-based secure event-driven serverless architecture for scalable digital civic participation platform.

Introduction: With the growing digitalization of urban governance and the increasing demand for transparency, sustainability and secure decision-making, the need for scalable and intelligent digital civic platforms has been raised. However, current e-participation systems are often plagued by challenges related to scalability, regulatory compliance, digital sovereignty and secure citizen authentication. The challenges are tackled in this paper by proposing an AI-enabled serverless architecture for next generation digital civic engagement. Methods: This study proposes an AI-based Secure Event-driven Serverless Participation Architecture (SESPA) for digital e-participation services based on the Citizen Participation Event Model (CPEM), where each citizen interaction is treated as an event within a continuous decision-making process. Architecture employs an event-driven serverless computing paradigm integrated with artificial intelligence modules for biometric citizen verification and anomaly detection. To satisfy the digital sovereignty requirements of the Republic of Kazakhstan, a hybrid data localization model is introduced that separates personally identifiable information from anonymized analytical events. The proposed dual-loop architecture stores sensitive citizen data within national infrastructure while enabling cloud-based processing of anonymized event streams for scalable analytics without violating regulatory requirements. Results: An experimental prototype was evaluated under workloads of up to 10,000 concurrent users. The results demonstrated stable latency across p50, p75, p95, and p99 percentile metrics, efficient scalability through provisioned concurrency, and reduced total cost of ownership compared with an equivalent Kubernetes-based deployment. Moreover, the addition of AI modules to the event-processing pipeline added little latency overhead and allowed for precise detection of anomalous and suspicious participation behavior in controlled experimental workloads. Discussion and conclusion: The proposed SESPA architecture effectively combines event-driven serverless computing, AI-assisted security mechanisms and hybrid data localization to provide a secure, scalable and regulation-compliant digital participation platform. The results demonstrate that the proposed framework offers a good technology foundation for next generation smart city applications by supporting high citizen engagement, regulatory compliance, digital sovereignty and intelligent decision-making, while maintaining high system performance and cost efficiency.