Physical AI startup RLWRLD raises $26M

RLWRLD, a physical AI startup developing robot foundation models for industrial environments, today said it has raised $26 million in Seed 2 funding.

This latest round brings the Seoul-based company’s total seed capital to $42 million, following its $14.8 million Seed 1 round in April 2025.

“Our Seed 2 round brings RLWRLD closer to partners who are actively deploying physical AI in industrial environments,” said Junghee Ryu, CEO of RLWRLD. “Physical AI only matters if it works on real job sites. By testing our models in some of the toughest industrial environments, we’re building systems meant for real operations first—before they ever make sense elsewhere.”

RLWRLD uses unpredictability to train its models

Unlike robotics systems trained primarily in clean, controlled lab settings, RLWRLD’s models are trained using high-precision, multimodal data collected directly inside real factories, warehouses, and service environments.

The company said its approach exposes the models to the unpredictability of live operations—crowded spaces, variable lighting, human interaction, and imperfect conditions—that are difficult to replicate in simulations.

RLWRLD said it plans to use large-scale multimodal data, advanced AI architecture, and global partnerships to create a core intelligence layer for robotics. It said its scalable, multi-sensor system captures complex demonstrations from diverse industrial settings, generating rich data for robust, adaptable models.

Projects progress from MOUs to validation

RLWRLD said it is executing proof-of-concept and robotics transformation projects with enterprise partners across logistics, retail, and service environments in Japan and South Korea. Several initiatives with major companies, including CJ Logistics and Lotte, have progressed from memoranda of understanding (MOUs) into joint industrial validation phases.

As part of these collaborations, RLWRLD is actively working with multiple strategic investors on joint projects that include using real-world operational data to train and validate its models.

“The future of logistics competitiveness depends not on basic automation, but on AI systems that can understand and reason about complex physical environments,” said a representative from CJ Logistics. “Through our collaboration with RLWRLD, we are working to deploy robot foundation models that can be applied directly to live warehouse operations and accelerate the transition toward AI-driven autonomous logistics.”

RLWRLD said it structured its Seed 2 round to expand its investor alliance in response to growing demand from enterprise partners seeking on-site validation and long-term collaboration. Participants included global venture firm Headline Asia, Z Ventures (the corporate venture capital arm of Z Holdings, Yahoo Japan–LINE), and Korea Development Bank.

In addition, strategic investors such as CJ Logistics, Kakao Investment, Lotte Ventures, Hanwha Asset Management, and Mirae Asset–Emart Investment Fund participated.

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