WIRobotics is betting that years of real-world movement data could shape the next generation of humanoid robots
Updated
May 19, 2026 5:10 PM
3D render of a person in various colours. PHOTO: UNSPLASH
Investor interest in humanoid robotics is continuing to grow as startups race to build systems capable of working alongside humans in real-world environments. That momentum was reflected after WIRobotics announced a KRW 95 billion (USD 68 million) Series B funding round to accelerate development of its humanoid robotics platform, ALLEX.
The Seoul-based startup said the funding comes roughly two years after its KRW 13 billion Series A round in 2024. JB Investment led the financing alongside investors including InterVest, Hana Ventures, Smilegate Investment, SBVA, NH Investment & Securities, Company K Partners, GU Investment and FuturePlay.
WIRobotics has spent the past several years building wearable robotics systems designed to assist human movement. The startup is now using that foundation to expand deeper into humanoid robotics and Physical AI, a category focused on AI systems that can interact with the physical world through movement, perception and manipulation.
Its humanoid platform, ALLEX, is being developed to support human-level object manipulation and interaction capabilities. The startup was recently selected for NVIDIA’s Physical AI Fellowship, a global robotics and AI development initiative aimed at supporting next-generation robotics research.
Rather than building humanoid systems entirely from scratch, WIRobotics is drawing on movement data collected through its wearable walking-assist robot, WIM. Over the past three years, the startup says it has built large real-world datasets around gait patterns, mobility and human movement control.
That wearable robotics business has also started showing commercial traction. WIM has sold more than 3,000 cumulative units and expanded into overseas markets including Europe, China, Türkiye and Japan. Revenue grew from KRW 560 million in 2023 to KRW 1.3 billion in 2024, then to KRW 2.79 billion in 2025. According to the startup, first-quarter 2026 revenue has already surpassed its full-year 2024 total.
The startup believes that real-world movement data collected through wearable robotics could become a competitive advantage as humanoid systems move closer to commercial deployment. WIRobotics is also expanding its global footprint alongside its robotics development efforts. The startup said it is establishing a North American entity in California while growing partnerships with overseas distributors and healthcare networks.
Its humanoid ambitions are moving into a more operational phase as well. Beginning later this year, WIRobotics plans to supply a research-focused version of its Mobile ALLEX platform to global research institutions and international partners for testing and collaborative development. The startup is also in discussions with a global automotive manufacturer around manufacturing-focused platform validation projects.
Yeonbaek Lee said: "This investment represents global recognition that the real-world movement data and control technologies accumulated through wearable robotics can evolve into next-generation humanoid robotics. We aim to accelerate the arrival of humanoid robots capable of interacting naturally with people".
Yongjae Kim added: "All investors from our previous Series A round participated again in this Series B financing, demonstrating strong confidence in WIRobotics' technological capabilities and growth potential amid intensifying global humanoid competition. Our mission is to realize humanoids capable of fundamentally human-like interaction and force control, driving a paradigm shift in high-performance manipulation technologies".
As competition intensifies across humanoid robotics, startups are increasingly trying to differentiate themselves through real-world deployment data rather than simulation alone. WIRobotics is positioning its wearable robotics business as the foundation for that transition, betting that years of human movement data could help shape the next generation of humanoid systems.
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Robots that learn on the job: AgiBot tests reinforcement learning in real-world manufacturing.
Updated
January 8, 2026 6:34 PM
A humanoid robot works on a factory line, showcasing advanced automation in real-world production. PHOTO: AGIBOT
Shanghai-based robotics firm AgiBot has taken a major step toward bringing artificial intelligence into real manufacturing. The company announced that its Real-World Reinforcement Learning (RW-RL) system has been successfully deployed on a pilot production line run in partnership with Longcheer Technology. It marks one of the first real applications of reinforcement learning in industrial robotics.
The project represents a key shift in factory automation. For years, precision manufacturing has relied on rigid setups: robots that need custom fixtures, intricate programming and long calibration cycles. Even newer systems combining vision and force control often struggle with slow deployment and complex maintenance. AgiBot’s system aims to change that by letting robots learn and adapt on the job, reducing the need for extensive tuning or manual reconfiguration.
The RW-RL setup allows a robot to pick up new tasks within minutes rather than weeks. Once trained, the system can automatically adjust to variations, such as changes in part placement or size tolerance, maintaining steady performance throughout long operations. When production lines switch models or products, only minor hardware tweaks are needed. This flexibility could significantly cut downtime and setup costs in industries where rapid product turnover is common.
The system’s main strengths lie in faster deployment, high adaptability and easier reconfiguration. In practice, robots can be retrained quickly for new tasks without needing new fixtures or tools — a long-standing obstacle in consumer electronics production. The platform also works reliably across different factory layouts, showing potential for broader use in complex or varied manufacturing environments.
Beyond its technical claims, the milestone demonstrates a deeper convergence between algorithmic intelligence and mechanical motion.Instead of being tested only in the lab, AgiBot’s system was tried in real factory settings, showing it can perform reliably outside research conditions.
This progress builds on years of reinforcement learning research, which has gradually pushed AI toward greater stability and real-world usability. AgiBot’s Chief Scientist Dr. Jianlan Luo and his team have been at the forefront of that effort, refining algorithms capable of reliable performance on physical machines. Their work now underpins a production-ready platform that blends adaptive learning with precision motion control — turning what was once a research goal into a working industrial solution.
Looking forward, the two companies plan to extend the approach to other manufacturing areas, including consumer electronics and automotive components. They also aim to develop modular robot systems that can integrate smoothly with existing production setups.