AI that learns how the world works
Scientific world models for physical and industrial systems
Our team combines scientific machine learning, compositional AI, atmospheric science, and production engineering.
Research grounded in science and engineering
Beyond prediction
discover reusable dynamical processes and compose them to reason beyond the historical record
- scientific machine learning
- compositional world models
- neural simulation of physical systems
- weather and climate intelligence
- reliable AI beyond the training distribution
Pasquale Minervini, PhD
Chief Technology Officer (CTO)
Professor of Natural Language Processing at the University of Edinburgh and ELLIS Scholar. His research spans compositional reasoning, discrete latent-variable learning, and self-improving AI systems—core ingredients for models that discover and reuse dynamical processes.
Raymond Lee
Head of Engineering (HoE)
Former Amazon engineer with over 10 years of experience in industrial Machine Learning and Recommendation Systems. Leads the engineering team and oversees development and deployment of client solutions.
John Westcott
Chief Executive Officer (CEO)
Former senior executive at General Electric and SoftBank, with experience managing a $150 billion portfolio and scaling SaaS businesses internationally. Provides strategic and commercial leadership.
Offices
Edinburgh
UK
Milan
IT
San Francisco
US