Neolix Completes Series E Round of Nearly 400 Million Dollars

Neolix has officially completed a Series E funding round of nearly 400 million dollars, as reported by Leiphone. The autonomous driving technology company secured the capital to accelerate its global expansion and the commercial deployment of its services. The investment round was co-led by Boyu Investment and a national-level fund. Participating investors included the Alibaba AEF NextGen Hong Kong fund, Monolith Capital, IDG Capital, Vertex Growth, a subsidiary of Temasek, Huaying Capital, GAC Capital, Jinding Capital, Langma Peak Venture, CP Robotics, Linghang Xinjie, and Gaohu Capital. Existing shareholders who continued to invest in the round include Stone Venture, Xingchen Capital, Gaosheng Investment, Yunqi Capital, SoftBank Asia, Yizhuang Guotou, Zhechuang Investment, Huixin Fund, Dinghui VGC, Chaoxi Capital, Yaotu Capital, Shanshui Capital, and Gaorong Venture. Gaohu Capital served as the exclusive financial advisor for this transaction. This financing represents the largest single investment in the domestic autonomous driving sector this year. Neolix has now raised a cumulative total exceeding 10 billion yuan, placing it at the top of the unmanned delivery vehicle industry by funding scale. Over the past year, the company has maintained the world's largest fleet of autonomous vehicles. Its delivery operations have expanded from e-commerce logistics to a broader capacity network serving various shippers, helping clients reduce costs and increase efficiency.

Technologically, Neolix has developed a vision-based end-to-end large model. It utilizes a unified architecture combining cloud, edge, and vehicle models to create a data flywheel for operations, data, and algorithms, which drives operational upgrades and efficiency improvements. The company has also led the industry in global deployment, achieving the largest overseas delivery scale for unmanned vehicles. It has rolled out services in the Middle East, Europe, East Asia, Southeast Asia, and Australia. In 2026, policy support for the sector has accelerated. In July, the Ministry of Transport indicated plans to promote digital and intelligent logistics and pilot the standardized application of unmanned delivery vehicles during the 15th Five Year Plan period. In August, the National Development and Reform Commission and the Ministry of Transport issued an implementation plan for logistics network construction, explicitly promoting the commercial operation of unmanned delivery and low-altitude logistics equipment. In September, nine departments including the Ministry of Industry and Information Technology issued a plan for the development of intelligent connected new energy vehicles, which mandates multi-scenario application pilots for functional unmanned vehicles. Boyu Investment stated that Neolix is a leading enterprise that has pioneered a national capacity network using Robovans. The investor noted that the company has achieved scaled delivery in multiple overseas countries, validating the global competitiveness of its products.

Boyu Investment expressed its intent to support Neolix in consolidating its industry position and helping leading Chinese technology companies expand globally. Yu Enyuan, the founder of Neolix, stated that autonomous driving technology is becoming a pillar of modern economic circulation by creating real economic net benefits in daily logistics. He said the company aims to build an efficient and reliable unmanned vehicle capacity network to drive global unmanned logistics infrastructure with artificial intelligence. He added that the team will focus on long-term development in each city, using reliable products and services to return the trust of investors and industrial clients. Following the completion of this round, Neolix will direct funds toward two main areas. First, it will deepen its refined operational network and accelerate the localization of service hubs in major global regions to build a more efficient customer fulfillment network. Second, it will increase investment in the data training loop for its end-to-end large model to improve autonomous driving safety and vehicle performance while reducing the total cost of ownership over the vehicle's lifecycle.