Worldmodeldata

Summary active Updated Jul 6, 2026

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Location Cambridge, United Kingdom
Founded 2025
Latest Stage Seed
Total Raised £7M

About

Worldmodeldata is a Cambridge, UK-based AI data infrastructure startup building a training-data library sourced from modern video games for world models, vision-language-action (VLA) systems, and physical AI. The company argues that gameplay footage captures rich, dynamic human-in-the-loop interaction data at a scale unavailable in real-world video, and is aggregating and structuring these datasets under commercial agreements with game studios. Founder and CEO Rhea Loucas, a serial entrepreneur, has set a target of accumulating one million hours of curated gameplay data by the end of 2026 — the current largest comparable database contains roughly 40,000 hours. Lord Richard Allan, former Meta VP of Public Policy, joined the board as chairman on emergence from stealth 123.

Funding History

Date Round Amount Lead Co-investors
2026-07-06 Seed £7M Iona Star Capital (not disclosed in accessed sources) 123

Proceeds will fund product development, team expansion, and further data-sourcing agreements with game studios 12.

What Investors Say

No independently sourced investor quotes incorporated at this time.

What Founders Say

No independently sourced founder testimonials found at this time.

Sources


  1. UKTN, “Worldmodeldata raises £7m to accelerate gaming data for AI training,” July 6, 2026. Accessed July 2026. https://www.uktech.news/funding/worldmodeldata-raises-7m-to-accelerate-gaming-data-for-ai-training-202607

  2. Business Cloud, “Worldmodeldata raises £7m to unlock gaming data for AI training,” July 2026. Accessed July 2026. https://businesscloud.co.uk/news/worldmodeldata-raises-7m-to-unlock-gaming-data-for-ai-training/

  3. Tech Funding News, “Ex-Meta policy VP joins board as Worldmodeldata raises £7M seed. Can it hit 1M hours of data before its rivals do?,” July 2026. Accessed July 2026. https://techfundingnews.com/worldmodeldata-7m-seed-ai-training-data-video-games/