Neolix debuts AI-powered autonomous delivery platform
During the annual CES 2026 tech conference, autonomous technology company Neolix has unveiled what it calls its AI-powered autonomous delivery platform RoboVan X1, designed to address ‘last-meter’ delivery challenges.
The company says most delays and costs occur in the final 100 meters of the delivery, adding that X1 is designed to transition seamlessly from street-level delivery to indoor environments, including lobbies and doorways, reducing the need for manual handoffs and enabling door-to-door autonomous delivery. Neolix said the X1 allows a single autonomous system to manage deliveries from distribution centers through to the customer’s doorstep.
The company said the system is built on deep learning and foundation model technologies, the system supports end-to-end operations including order processing, route planning, and real-time vehicle dispatch.

According to the company, its platform is capable of managing fleets of up to 100,000 autonomous vehicles and uses dynamic resource allocation algorithms to respond to fluctuations in urban delivery demand, improving fleet efficiency by more than 30%.
Neolix, headquartered in China, claims that it became the first company in 2025 to deploy mapless L4 autonomous driving technology at commercial scale. The company says in the release that its system combines advanced perception with AI-driven decision-making to enable centimeter-level positioning and real-time responses in complex urban environments.
The company added that eliminating reliance on high-definition maps reduces deployment costs and shortens rollout timelines, supporting faster scaling across new cities and regions. The RoboVans are designed to operate in mixed traffic, pedestrian-dense environments, and adverse weather conditions.
Have your say
This is a moderated forum. Comments will no longer be published unless they are accompanied by a first and last name and a verifiable email address. (Today's Trucking will not publish or share the email address.) Profane language and content deemed to be libelous, racist, or threatening in nature will not be published under any circumstances.