Neolix Scales RoboVan-as-a-Service Model, Accelerates Expansion Across China and Overseas

BEIJING, March 30, 2026 /PRNewswire/ -- Neolix, a global provider of autonomous logistics solutions, today shared an update on the progress of its RoboVan-as-a-Service (RaaS) model, marking a key step forward in the commercialization of on-demand autonomous logistics.

The company's on-demand delivery service has now completed more than 1.5 million orders and accumulated over 40 million kilometers of autonomous driving, following rapid deployment across multiple cities in China. In Qingdao, where the model was first scaled, Neolix has established one of the largest autonomous delivery fleets operating within a single city, with peak daily order volumes exceeding 6,500.

The milestone reflects a broader shift in how autonomous delivery is deployed and operated. Unlike earlier models that relied on fixed routes or hardware purchasing, Neolix's RaaS approach introduces an on-demand, network-based service model. Through a mobile interface, users can request an autonomous vehicle in real time to complete point-to-point deliveries, similar to ride-hailing.

Building on this progress, Neolix is entering a new phase of expansion. The company plans to extend its RaaS operations to 50 cities across China within the year, while also advancing international pilots in the United Arab Emirates, South Korea, Singapore, and Portugal. These deployments are intended to explore how the model can be adapted to different urban environments and regulatory frameworks, laying the groundwork for broader global rollout.

The model was first piloted in Qingdao in partnership with Didi Freight in mid-2025 and is designed to better address fragmented, high-frequency logistics needs, particularly among small and medium-sized businesses. By enabling flexible routing and usage-based pricing, the service lowers the barrier to adopting autonomous delivery and, in many cases, reduces delivery costs by around 50% compared with traditional delivery models, while also improving service reliability.

This approach targets a large but historically underserved segment of the urban logistics market. Across China, urban distribution represents a multi-trillion-renminbi market, yet a significant portion of demand comes from small merchants, wholesalers, retailers, and local service providers whose needs are often irregular, time-sensitive, and difficult to standardize. Neolix's RaaS model is designed to accommodate these dynamics by providing a shared, on-demand delivery network that can support diverse use cases, ranging from retail replenishment and fresh goods distribution to pharmaceutical and manufacturing deliveries, with vehicles operating around the clock to support continuous urban supply chains.

Underlying the model is a combination of vehicle-side autonomy and cloud-based system intelligence. Neolix has deployed L4 autonomous driving technology at scale, enabling vehicles to operate in complex urban environments without reliance on high-definition maps, which supports faster deployment in new locations. At the same time, a centralized dispatch and coordination system connects vehicles into a unified network, allowing for real-time scheduling and dynamic route optimization across large volumes of orders. As fleet size and geographic coverage expand, this networked approach improves overall efficiency, shortens response times, and reduces marginal costs, reinforcing the scalability of the service.

"As autonomous driving technology matures, the focus is increasingly shifting from individual vehicles to integrated service networks," the company said in a statement. "Our goal is to make autonomous delivery accessible as a shared infrastructure, enabling more efficient urban logistics and supporting the digital transformation of city supply chains."

With continued growth in both fleet scale and operational capability, Neolix expects its RaaS model to play a growing role in shaping the next generation of urban logistics, providing a more flexible and scalable alternative to traditional delivery systems.

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