Gigaton

Gigaton, founded in 2020 as an academic spin-out from UCL and the University of Cambridge, develops autonomous AI control and optimization systems for energy-intensive industries. Its technology is aimed at cement, steel, glass and chemicals - sectors responsible for roughly 8 billion tons of carbon emissions a year - where it applies machine learning to both the control and optimization layers of plant operations.

The company's core product, Self-Learning Control, sits at the heart of plant operations and directly controls actuators. The system is designed to explain its actions to operators and to learn as plant conditions change; explainability and operator trust are central to its design. Technical work spans AI/ML control systems, reinforcement and self-learning control, industrial optimization and actuator control.

At customer sites, the system has delivered a 4% reduction in fuel cost index and a 33% reduction in C3S variability. Gigaton raised $26 million in a Series A round to scale this work.

The company describes its focus as one of the more challenging control and machine-learning problems in industry, with a mission of cutting gigatonnes of carbon emissions from the world's largest emitting sectors.