Ele.me officially launched "Xiao E," China's first rider-side AI assistant powered by large language models. This AI-powered tool reshapes the rider's work environment, improving both operational efficiency and safety. The feature has initially been rolled out in four cities: Wuxi, Shenyang, Foshan, and Suzhou, covering riders using the Fengniao Zhonbao app.
According to Ele.me's technical team, "Xiao E" leverages natural language processing (NLP), multimodal interaction, and real-time data analysis, deeply integrating into the entire delivery process. Its core functions include three aspects: hands-free operation via voice interaction—riders can simply say "Xiao E Xiao E" to accept orders, confirm arrival, check promotions, and perform other frequent operations, reducing manual clicks and boosting daily operational efficiency by approximately 30%; proactive risk warnings based on real-time rider location, order status, and environmental data—this includes alerts for heavy rain, sudden road closures, and platform benefit notifications, helping riders avoid potential delivery risks; and dynamic order acceptance strategy suggestions—by integrating historical order data and regional order heatmaps, it recommends personalized analyses such as "high-volume periods" and "optimal delivery radius," helping riders optimize their income structure.
Ele.me's product manager stated that this intelligent assistant doesn't simply replace manual operation but deeply integrates "AI + scenarios" to address pain points in complex delivery environments. For example, during peak order times, riders can use voice commands to simultaneously handle navigation switching and status updates for multiple orders; in the event of unexpected traffic control, "Xiao E" can generate alternative routes based on real-time traffic conditions, avoiding late delivery penalties. Furthermore, the platform will continuously iterate the model based on user feedback and plans to expand to value-added services such as rider health monitoring and intelligent insurance recommendations in the future.