Silicon Valley-based QCraft successfully closes a $100 million Series D funding round, strengthening its push toward advancing physical artificial intelligence (AI) for autonomous driving and mobility applications. The round was backed by a consortium of investors, including Ningbo Ninghai Xingtaihe Fund, Wonderland Capital, Liangxi Science and Innovation Industry Investment Fund Partnership—managed by Broad Vision Funds—along with strategic investors from leading automotive OEMs and electronics component suppliers.
The newly secured capital will be allocated to two primary areas: accelerating frontier research in physical AI, particularly in world models and reinforcement learning, and enhancing the company’s organizational strength through global talent expansion.
James Yu, Chairman and CEO of QCraft, emphasized the timing of the investment, describing 2026 as a crucial turning point in AI evolution. He noted that the industry is moving beyond human-like intelligence toward superhuman capabilities, with the most transformative opportunities expected to emerge in real-world applications. Autonomous driving, he added, represents one of the most direct pathways to unlocking the potential of physical-world AI.
In line with this vision, QCraft is intensifying its focus on Level 4 (L4) autonomous driving and general physical AI systems, while also accelerating its global expansion strategy. The company continues to invest heavily in developing advanced world model frameworks and reinforcement learning technologies.
QCraft’s progress is reflected in the growing adoption of its solutions. Its QPilot intelligent driving system has now been deployed in over one million vehicles across nearly 30 production models, supported by partnerships with around 10 leading automotive OEMs. The company’s QPilot Pro platform, which delivers advanced urban Navigate on Autopilot (NOA) capabilities on a single 128 TOPS chip, has garnered significant industry recognition for its performance.
Looking ahead, QCraft plans to expand its technology footprint further, with its NOA capabilities expected to be integrated into more than 50 additional vehicle models in 2026. The company is also preparing to unveil its world model and reinforcement learning platform, marking a key step toward enabling general-purpose physical AI.
In the autonomous driving landscape, QCraft has established a notable presence in the L4 logistics segment through its “Operations from Day One of Production” model. These solutions are already commercially deployed in cities such as Jinhua, Wuhu, and Ningbo. Additionally, the company is set to launch a Robotaxi pilot program in 2026, with plans for full-scale deployment by 2027.
