Japan’s Algomatic Dynamics Raises $34 Million for Robot Hands and Physical AI
The Japanese startup plans a 2026 robot-hand platform release, with customers, pricing and performance data undisclosed.

TOKYO — Japanese robotics startup Algomatic Dynamics said it raised 5 billion yen ($32.5 million) from DMM.com, an e-commerce and internet company, to finance hardware development and computing resources for robot training.
The company announced the financing Sept. 9, describing it as its first funding round since its establishment April 27. It did not disclose the financing structure, valuation or other terms.
Algomatic Dynamics was formed following a restructuring of Algomatic, an AI company in the DMM group, according to the announcement. Its most immediate product plan is a multifingered AI robot-hand platform that the company intends to unveil in Japan by the end of 2026.
Algomatic Dynamics said it will work with companies and research institutions on validation tests as it moves toward applications in industrial and everyday settings. The release does not identify those prospective partners or describe any confirmed commercial deployments.
Algomatic Dynamics plans to combine robot hardware with motion-data collection, model training and support services. The company says it can convert video of skilled workers’ hand movements into training data, capturing details such as timing, applied force and where a worker looks while completing a task.
The company claims its hand technology can adjust its grasp to rigid components, soft materials and irregularly shaped objects such as food. It also says its locomotion technology combines model-based control, reinforcement learning and motion-capture data to help bipedal robots negotiate uneven ground, steps and slopes. Those capabilities have not been independently evaluated.
Algomatic Dynamics has not released the specifications or price of its planned hand platform. It also has not identified paying customers, disclosed unit deliveries or published comparative testing that would establish how its technology performs against other robot-hand and control systems.
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