Gigaton has raised $26m (£19.3m) in Series A funding through a round led by Plural.
Gigaton builds autonomous, self-learning AI control software for energy-intensive industries. Its platform simulates, controls and improves complex industrial processes, reducing fuel costs, cutting emissions and enabling a new generation of resilient, intelligent plant operations.
Soaring energy costs, increased complexity from new fuel types and market volatility are squeezing margins across cement, steel, glass and chemicals, yet most plants still run on old control systems that depend on manual intervention.
Gigaton says while China is already building fully autonomous ‘dark plants’ – facilities that run without on-site operators – the rest of the world risks falling behind. The startup aims to address this need with its self-learning technology that operates deep within plant infrastructure.
The tech simulates process behaviour and forecasts the impact of each action before it is taken, allowing it to autonomously adjust key parameters.
The round included participation from 2150, Semapa Next and existing investors Planet A Ventures, Cambridge Enterprise Ventures, UCL Technology Fund managed by AlbionVC with UCL Business, and Clean Growth Fund.
The new investment will fund a five-times increase in the team and an expansion into steel, glass and chemicals.
“Every cement executive I speak to is facing the same challenges: costs they struggle to control, carbon they struggle to reduce, and plants that weren’t built for the world they’re operating in today,” says Josh Vernon, CEO of Gigaton.
“The underlying software infrastructure most plants run on today was never built to manage the complexity plants are forced to deal with today. We have built Gigaton to deliver real cost and carbon savings now while building the AI infrastructure these industries need in a fully autonomous future.”
