Gigaton builds autonomous AI control and optimization systems for energy-intensive industries, among them cement, steel, glass and chemicals. Founded in 2020 and spun out of UCL and the University of Cambridge, the company targets industrial sectors responsible for roughly 8 billion tonnes of carbon emissions a year. It raised $26 million in a Series A round.
Its product, Self-Learning Control, is an AI system that sits at the core of plant operations, applying machine learning to both control and optimization layers. It works at actuator level, explains its decisions to plant operators, and adapts as operating conditions change. Reported results at customer sites include a 4% reduction in fuel cost index and a 33% reduction in C3S variability. Named customers include Heidelberg Materials, Holcim, Cimsa, Secil, Cimpor and Mannok.
The technical work spans autonomous and adaptive control systems, process control, industrial optimization and explainable AI. The company describes the problem it is working on as one of the more difficult in control and machine learning, with a stated aim of moving heavy industry toward fully autonomous operation.
