Worldmodeldata, a Cambridge-based startup building a database of video game-generated training data for next generation AI, has raised £7m in seed funding as it emerges from stealth. The startup says world models – an AI system’s internal understanding of how the world works – will form the backbone of the
Kirstie Pickering
Worldmodeldata, a Cambridge-based startup building a database of video game-generated training data for next generation AI, has raised £7m in seed funding as it emerges from stealth.
The startup says world models – an AI system’s internal understanding of how the world works – will form the backbone of the next generation of AI.
Rather than reacting to inputs, Worldmodeldata’s world models learn how things look, interact and change over time – and this allows them to predict what will happen next and plan actions accordingly to operate safely in complex environments. However, these models are only as capable and robust as the data they are trained on.
Worldmodeldata says it overcomes this bottleneck by aggregating and structuring rich datasets from modern video games that capture real human behaviour and interactions in complex, dynamic environments.
The firm gives customers, such as frontier labs building world models, physical AI systems and robotic companies, the foundation for training models that need to understand dynamics, predict outcomes and make safer decisions in the real world.
This data is sourced from real gameplay in titles built on engines such as Unreal and Unity. It is acquired via formal licensing agreements that allow the gaming community and developers to monetise their gameplay and assets built with Worldmodeldata, rather than using web scrapers.
The funding round was led by Iona Star Capital, a London-based venture capital fund focused on early-stage companies operating at the intersection of AI, data and technology.
Worldmodeldata aims to build a data library of one million hours by the end of 2026. The funding will help advance this goal by fuelling product development, team expansion and the securing of data-sourcing agreements.
“World models represent a fundamental paradigm shift in AI, but progress like this needs fuel: internet-scale data to help AI systems make predictions and reason in physical environments,” says Rhea Loucas, founder and CEO at Worldmodeldata.
“Such a comprehensive dataset does not yet exist; however, video games, as safe, controlled environments, are the perfect setting for generating the action-conditioned data needed to train the next generation of AI at the required scale. Worldmodeldata is built to bridge that gap.”
