Yaole raises Pre-A+ round, targets 10x revenue growth in 2026
What's the deal? Chinese flexible tactile sensing startup Yaole TechnologyDealroom has a profile for this one. Try Dealroom → has closed a Pre-A+ round led by Dinghe Gaoda, with listed companies Changshu Automotive Trim and Zulong Entertainment participating. The funds will go toward research into flexible fabric sensing, product upgrades, and scaling production of its data gloves.
What does it do? Yaole uses flexible fabric as a hardware entry point to collect and pre-process real physical interaction data for embodied AI and world models. Its coming data glove weaves sensors directly into the fabric using a proprietary "metal yarn plus sandwich matrix" design, eliminating the layer slippage and noise that plague film-based rivals.
Why now? The industry's bottleneck has shifted from robot hardware to a data shortage. Per the China Embodied Intelligence Industry Development Report, global high-quality real physical interaction data totalled about 500,000 hours in early 2026, while training a general embodied model needs at least tens of millions of hours — a gap of more than 90%.
The tactile gap: Unlike vision and text, touch data can't be scraped online. Simulation struggles to reproduce pressure distribution, friction, and material deformation, so real human-captured data remains essential. Data gloves have emerged as a key path to fill that void.
What's the endgame? Founder and chief executive officer Lyu Liyun, formerly a chief architect at Harman, positions the glove as a "consumable" — cheap, replaceable, and accurate over its lifespan rather than built to last a decade. Yaole delivers not just hardware but data cleaning, calibration, and time-axis alignment services, cutting customers' training costs. It expects the glove business to make up more than half of revenue in 2026, with full-year revenue growing 10x.
What could go wrong? Competition is intensifying, with domestic electronic-skin glove makers multiplying across printed film, visuotactile, and fabric approaches. Lyu argues the winner will be whoever first achieves mass production and cost reduction while keeping data accurate, pointing to Yaole's automotive-grade reliability and supply chain experience as its edge.
The signal: Investors say the market is shifting from flashy robot bodies to asking where real interaction data comes from and whether it can scale. As Dinghe Gaoda managing partner Wang Ying framed it, Yaole is "the key piece" for physical interaction data — a bet that China's engineering depth can turn human touch into a trainable data pipeline for the global Physical AI race.
Image credit: Generated with Gemini
