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Pangbote raises hundreds of millions of yuan Series B for AI sports training

AI summary

AI sports hardware company Pangbote has closed a Series B round of several hundred million yuan, led by Shanghai Guotou Xiandao Fund with Yuanhe Puhua and Pudong Venture Capital participating and existing investor BlueRun Ventures China increasing its stake, according to 36Kr; Gaohu Capital was exclusive financial adviser. The company had previously completed three Series A rounds. Proceeds will go toward its sports large model, motion vision and training-decision technology, plus global expansion and additional sports categories. Starting from table tennis ball machines, Pangbote built a “hand-eye-brain” architecture: its PACE tennis ball robot raised more than $2.7 million on Kickstarter from October 2024, and its Aura all-in-one AI coach robot, released in May 2026, passed $1 million in five hours and more than $4 million in total crowdfunding. The company says it has over 300,000 global users, more than 2 billion cumulative serves, and 1 million table tennis plus over 200,000 tennis ball-trajectory datasets; on Sept. 28 the Australian Open named it an official partner, official ball machine partner and official ball machine supplier to the Australian National Tennis Academy.

In-depth insight

The round shows investors still backing AI hardware that pushes large models into physical training, though the sports model's real coaching value and data moat remain unproven.

作者|黄楠

编辑|袁斯来

硬氪获悉,AI体育硬件公司「庞伯特」近日完成数亿元B轮融资,由上海国投先导基金领投,元禾璞华、浦东创投等跟投,老股东蓝驰创投持续加注。高鹄资本担任独家财务顾问。

此前公司已连续完成三轮A轮系列融资,神骐资本、明势创投、蓝驰创投、锦秋基金、华创资本及成为资本等头部机构集体参与。

融资资金将重点投向AI体育大模型、运动视觉与训练决策技术研发,拓展全球市场,完善海外渠道与本地化品牌运营;落地更多运动品类新品,扩大技术平台复用边界。公司长期目标是普及专业运动训练服务,让普通用户也能获得专业级训练体验。

庞伯特最早从乒乓球场景切入,逐步建立起覆盖发球执行、视觉感知、运动分析和训练决策的“手、眼、脑”一体化能力,在行业内率先把自研体育大模型落地至智能发球机硬件产品,并将这套技术能力复用到网球等其他运动品类。

#Pangbote#Aura#PACE#Shanghai Guotou Xiandao Fund#Yuanhe Puhua#Pudong Venture Capital#BlueRun Ventures China#Gaohu Capital#Australian Open#Australian National Tennis Academy#Kickstarter

Original · 11 min readRead the original
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