Embodied-data startup SCALEFORCE closes two funding rounds in 40 days to build physical-AI infrastructure

Embodied-intelligence data infrastructure startup Yuanpoint Technology (SCALEFORCE) has completed a new funding round worth tens of millions of yuan, according to a report from QbitAI. Investors include a top domestic embodied-AI industry player, Hengxu Capital and Kailian Capital, marking the company's second round within 40 days and tens of millions of yuan raised in total.

The proceeds will mainly fund iteration of its MatrixOS physical-AI operating system, construction of a large-scale data production network, and team expansion. Founder Guo Jiangliang says the embodied-AI race has entered a second half defined by data and intelligence, and the company aims to supply the industry with high-quality data products drawn from real physical-world scenarios.

Guo is a founding member of Baidu Intelligent Cloud and a former technology vice president at AInnovation, where he built out the industrial large-model and embodied-AI technology stack. The team describes itself as battle-tested practitioners who have spent years working directly with data and revenue.

The market context is striking: domestic embodied-AI funding reached 93.5 billion yuan in the first half of 2026, up roughly five-fold year over year, while globally available high-quality physical interaction data totals only about 500,000 hours — a gap of over 99% versus the tens of millions of hours needed for general-purpose embodied models.

The company's core product is MatrixOS, positioned as an embodied-AI data infrastructure with data collection, processing and distribution capabilities, and it says it has already built a closed data flywheel running from collection to application.

On commercialization, a tens-of-millions-level data order from lighthouse customer Tashi Zhihang is fully underway — its A-series robots entered an Aptiv factory with Yuanpoint's data services — and the company has built deep partnerships with world-model companies such as Zhi Zai Wu Jie and leading embodied-AI robot makers.

On the ecosystem side, Yuanpoint has joined Huawei's Ascend computing ecosystem as one of its first global open-source contributors of embodied-AI and world-model data and algorithm pipelines, and is a founding member of Xinhuanet's "Robot+" real-world training initiative. It is also collaborating with Peking University and Beihang University on frontier embodied-AI research.

Industry observers call 2026 the "first year of embodied data", with 2027 to 2029 seen as the key window for large-scale humanoid robot commercialization. In a race where data decides intelligence, whoever builds high-quality data infrastructure first is best positioned to lead.