RLWRLD

RLWRLD Inc. is a physical AI startup that develops robotics foundation models (RFMs) to enable robots to operate autonomously in dynamic, real-world environments. Founded in 2024 by serial entrepreneur Jung-hee Ryu, the company is headquartered in Seoul, South Korea, with an office in Tokyo, Japan. Ryu previously founded the computer vision company Olaworks, which was acquired by Intel in its first-ever acquisition of a Korean startup.

The company's founding team includes notable figures such as KAIST Chair Professor Jinwoo Shin as Chief Scientist, a former CTO of Kurly, a Kakao engineering lead, and a former BCG partner. In April 2025, RLWRLD announced a $15 million seed funding round with investments from major industrial corporations like LG Electronics, SK Telecom, KDDI, ANA Holdings, and Mitsui Chemicals, as well as venture capital firms including Hashed and Global Brain. This funding is intended to expand its data pipelines and advance its robotics foundation model stack.

RLWRLD's core technology focuses on creating AI that learns from real-world sensor data, robotic systems, and industrial workflows, as opposed to the text, code, and image data used by many generative AI models. This allows robots to reason and act autonomously in settings such as factories, warehouses, and logistics hubs. The platform is built on three pillars: an embodied model architecture for real-world intelligence, industrial-scale data pipelines from East Asia's manufacturing sector, and plug-and-play infrastructure that integrates with existing robotics systems. The company aims to develop advanced capabilities, including five-finger dexterity for complex manipulation tasks. RLWRLD collaborates with academic institutions like KAIST and Seoul National University, and robotics manufacturers such as WIRobotics and Rainbow Robotics.

Keywords: Physical AI, robotics foundation models, embodied intelligence, autonomous robots, industrial automation, manufacturing AI, real-world data, dexterous manipulation, computer vision, sensor data, logistics automation, warehouse automation, Jung-hee Ryu, Jinwoo Shin, machine learning, deep learning, plug-and-play robotics, human-robot collaboration, AI research, industrial workflows