OriginFlow - 渊澈太初
Beijing embodied-AI startup using non-invasive sEMG neural interfaces to turn human muscle signals into robot training data.
OriginFlow is a Beijing-based embodied-intelligence startup founded in 2025 by Qin Shendao, a doctoral student at Tsinghua University, to build the 'human intelligence layer' for embodied AI and robotics. The company pioneered a technology paradigm it calls NeuroScale, which uses a non-invasive motor neural interface to capture surface electromyography (sEMG) signals generated by human muscle contractions.
These neural-muscular signals are encoded by OriginFlow's proprietary foundation model, PULSE, to reconstruct native, continuous multimodal information such as hand pose, exerted force and haptic feedback. By collecting fine-grained human operation data through a proprietary EMG acquisition kit, OriginFlow aims to solve one of the hardest problems in robotics, dexterous and force-aware manipulation, by giving robots high-quality demonstration data that conventional vision-only or teleoperation methods struggle to provide. The company is building out two primary application domains. In industrial manufacturing, it partners with leading high-end manufacturers to jointly establish scenarios for industrial embodied-data collection. In home services, it works with partners such as 58 Group to gather large volumes of real human operation data across high-frequency household tasks including clothing organization, cleaning and kitchen work. OriginFlow attracted strong early investor interest, completing angel, strategic and Pre-A1 rounds within roughly five months of launch for cumulative funding exceeding CNY 500 million, with backers including BlueRun Ventures and Oasis Capital.
The company positions neural-muscular data acquisition and its PULSE model as core infrastructure for training the next generation of manipulation-capable embodied AI and humanoid systems.
Primary type & automation activities this supplier delivers:
Company Facts
Founded
2025
Primary Role
Software/Algorithm
Company Size
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Primary Region
Asia-Pacific
Annual Sales
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Funding Stage
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Funding Total
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Roundtable Forum: The Real Landscape of AI Venture Capital Beyond Consensus
In a recent roundtable discussion on the evolving landscape of artificial intelligence (AI) investment, industry leaders emphasized the importance of acting ahead of consensus to seize opportunities. The forum featured prominent figures such as Zhu Tianyu, managing partner at BlueRun Ventures, and Qin Shentao, founder and CEO of OriginFlow, who shared insights on their early investment strategies. Zhu, who joined BlueRun in 2009, highlighted his early investments in successful companies like Li Auto and Genspark, noting that he made quick decisions based on a structured understanding of global challenges rather than just project details. He expressed confidence in OriginFlow’s potential, which focuses on non-invasive neural interfaces for embodied intelligent robots, aligning with key trends in artificial general intelligence (AGI), robotics, and 3D interaction. Qin, a Tsinghua University PhD, explained that OriginFlow aims to revolutionize how intelligent systems interact with the physical world, addressing a significant gap in data collection and processing. Within just five months of operation, the company secured over 500 million RMB in funding, demonstrating strong market interest. Both leaders acknowledged the challenges of navigating the current AI investment climate, characterized by rapid funding influxes and potential market bubbles. They stressed the need for investors to discern genuine innovation from fleeting trends, emphasizing that true value lies in solving fundamental problems rather than chasing hype. As the discussion concluded, they reiterated their commitment to fostering groundbreaking advancements in AI and embodied intelligence.
Post-00s Entrepreneur Secures 500 Million Funding: Can NeuroMuscular Tech Solve Robot Control Challenges?
OriginFlow, a data technology firm founded by 25-year-old Tsinghua University PhD student Qin Shentao, has successfully secured over $500 million in funding to advance its NeuroScale product. This innovative technology employs surface electromyography to accurately capture human motion intent and force parameters, aiming to enhance robotic precision. The company seeks to address a significant challenge in the robotics industry: the difficulty robots face in mastering fine motor tasks. By bridging the data gap in robotic training, OriginFlow's NeuroScale has the potential to transform the way robots interact with physical objects, paving the way for more sophisticated and capable robotic systems.
Robotic Control Neurotechnology Data Acquisition Artificial Intelligence
