Gasgoo Munich-UISEE (Beijing) Co., Ltd. and Shenzhen Xuncetech Technology Co., Ltd. have officially signed a strategic cooperation memorandum, according to Gasgoo. The partnership aims to build high-quality datasets for the autonomous driving sector, develop industry-specific small models and agents powered by a "Token factory," and explore new commercial models for Tokens. Together, the companies plan to advance full-scenario joint solutions, carving out a new path for intelligent upgrades in the autonomous driving industry.
Image source: UISEE
The battleground in autonomous driving has shifted from pure algorithm innovation to the scale and quality of data. UISEE, a provider of Level 4 autonomous driving solutions across diverse scenarios, has amassed massive, high-quality, structured, and well-annotated datasets through long-term commercial operations in airports, ports, mines, and factories. This has created a proprietary data flywheel for specific scenarios. Xuncetech, meanwhile, specializes in real-time data infrastructure and analytics. With its cloud-native unified data platform, the company offers end-to-end data services for AI applications and manages the full lifecycle of multi-source heterogeneous data.
Under the agreement, the partners will merge UISEE's real-world scenario data with Xuncetech's AI data services to construct high-quality industry datasets. They also plan to develop customized, vertical-specific small models and agents tailored for autonomous driving applications. Furthermore, the collaboration aims to facilitate the compliant circulation and monetization of data within the sector.
"The future battleground for AI lies in proprietary data, not public information," said Wu Gansha, co-founder, chairman, and CEO of UISEE. He noted that the partnership aims to leverage Xuncetech's data capabilities to accelerate the feedback loop between autonomous driving technology and real-world scenarios, injecting fresh momentum into the industry's long-term growth.
This cross-sector collaboration marks a significant step for both the autonomous driving and real-time data infrastructure sectors, representing an active exploration of data value in the era of Physical AI. Looking ahead, both companies plan to push the technical boundaries and commercial scenarios of autonomous driving, supporting the intelligent transformation of the broader industry.
