An Intelligent and Scalable: AI Based QuickServe Service Marketplace for Real?Time Urban Service Management

On‑demand service marketplaces have become an integral part of modern urban life by enabling users to access professional services in a convenient and time‑efficient manner. However, existing platforms often suffer from inefficient provider selection, limited transparency during service execution, delayed responses, and insufficient real‑time coordination. These limitations reduce user satisfaction and erode trust in service platforms. This paper presents AI‑Based QuickServe, a comprehensive intelligent service marketplace that integrates artificial intelligence, geolocation services, and real‑time communication technologies to address these challenges. The proposed system includes AI‑assisted request understanding using image analysis, a multi‑criteria provider matching algorithm combining distance, availability, reliability, and timeliness, and real‑time tracking using WebSockets within a secure, scalable architecture. Extensive functional evaluation with realistic workloads demonstrates improved matching quality, reduced response latency, and enhanced transparency while maintaining stable performance under concurrent usage. The system provides a robust foundation for next‑generation urban service ecosystems.