Electric Twin, an AI
platform developing synthetic audience models designed to simulate real-world
human thinking and behaviour, has raised $14 million in funding. The total
includes a $10 million round led by Atomico, with participation from
LocalGlobe, Mercuri and Samos Investments, as well as several angel investors, including Marc Andreessen, Cal Henderson, Eric Salama, Tom Shinner and Louis
Mosley. The funding follows a previously undisclosed $4 million pre-seed round.
Founded by Dr Ben Warner and Alex Cooper, Electric Twin develops tools to help organisations
better understand their audiences and inform decision-making. By combining
real-world survey data with large language models, social science research and
machine learning, the platform creates synthetic audience models designed to
estimate how people may respond to messaging, product launches or strategic
proposals.
This approach is
positioned as an alternative to traditional research methods, which can be
time-consuming and costly and are often limited by fixed questionnaires and
sample sizes. Such constraints can leave decision-makers with incomplete
insights.
Electric Twin seeks to
address these limitations by transforming static research inputs into dynamic
digital audience models, enabling faster analysis and broader scenario testing.
The platform enables organisations to explore audience perspectives in greater
depth and evaluate ideas more efficiently.
Commenting on the
company’s origins, Alex Cooper, co-founder and CEO, said that their experience
leading during a crisis highlighted how often important decisions had to be
made with limited information. He explained that Electric Twin was created to
equip leaders with tools to better understand their audiences, interact with
them in real time and anticipate likely responses or behaviours.
The funding will support Electric Twin’s international expansion and
continued development of its prediction technology. As the company grows, it
plans to enhance its synthetic audience models and expand the range of
scenarios organisations can analyse, with the aim of making advanced
decision-support tools more widely accessible.