Carlinx Named to KPMG’s 8th “China Automotive Technology 50” List
On September 17th, 2025 KPMG China Automotive Industry Summit and the 8th Automotive Technology 50 List Conference were held in Shanghai. Carlinx was named to the list for its strategic foresight and proven results across core businesses — including Hyper Flow as the data foundation, Hyper Agent as the scenario-based AI platform, and Hyper Fleet as the fleet operations management platform — reflecting the industry’s strong recognition of Carlinx’s innovation and its value in empowering the automotive ecosystem.
Since its inception, the KPMG China’s Automotive Technology 50 list has served as a key barometer for identifying technology trends and recognizing outstanding innovators in automotive industry.The conference dedicated to uncovering Aand spotlighting uncover and spotlight the pioneering forces driving the industry’s digital and intelligent transformation.
As a provider of intelligent mobility solutions, Carlinx offers whole lifecycle services for vehicles，delivering intelligent, sustainable, and competitive solutions for global automakers and mobility service operators.
Powered by Hyper Flow , Carlinx enables collection and integration of multi-dimensional data across fleet operations, user behaviors, and environmental scenarios. This high-quality data supports AI application development and business system optimization, strengthening the foundation for the automotive industry’s intelligent transformation.
Hyper Agent, leveraging domain-specific data analytics, can be applied across automakers’ entire value chain — from R&D and production to sales and after-sales — supporting full-lifecycle data capabilities for intelligent vehicle development.
Additionally, Hyper Fleet addresses the operational and management needs of mobility service providers through real-time fleet tracking, driver behavior analysis, vehicle health monitoring, and intelligent scheduling optimization. These capabilities help optimize routes, identify risky driving behaviors, predict potential vehicle failures, and ultimately reduce operational costs while improving driving safety and efficiency.
