Our project is an AI-powered field service assistant designed to support elevator technicians across the full maintenance cycle. It integrates ticket data, service records, manuals, and telemetry signals to provide real-time troubleshooting recommendations, detects anomalous sensor data, offers voice-guided repair support, and generates structured incident reports. Key features include a multi-agent architecture and knowledge-grounded LLM responses. It enables end-to-end workflow automation — from ticket pick-up to final report generation to significantly improving efficiency, consistency, and technician experience on-site. Group member: Ruikang Tao, Ruifeng Nie, Zimeng Zhang, Yunxuan Liu, Tao Yu
