Gigaton, a London startup spun out of UCL and the University of Cambridge, has raised $26 million in Series A funding led by Plural, the company announced on June 3, 2026. The round, with participation from 2150, Semapa Next and existing investors, brings total funding to more than $35 million.
What does Gigaton's software actually control?
Gigaton builds autonomous, self-learning control software for energy-intensive industries. Per the round announcement, its platform simulates, controls and continuously improves complex industrial processes, reducing fuel costs and emissions in plants that still run on decades-old control systems dependent on manual intervention. Cement is the beachhead: Cambridge Enterprise's report says the company is deployed by several of the world's largest cement producers, including Adani Cement, Heidelberg Materials and Holcim, which are saving more than $1 million per year each in energy costs, a company-claimed figure.
The problem is structural rather than experimental, and the numbers explain why cement came first. A single cement kiln burns fuel continuously at temperatures above 1400 degrees Celsius, so small percentage improvements in how the kiln is controlled compound into millions of dollars per plant per year. Fuel is also the largest variable cost in cement production, which makes plant managers unusually receptive to software that promises to reduce it without capital equipment changes.
The constraints are structural. Energy-intensive plants face soaring energy costs, new fuel types and market volatility, while their control loops predate modern machine learning. Gigaton's approach replaces that legacy layer with software that learns each plant's dynamics and adjusts operations continuously, a category several competitors are also chasing with different degrees of autonomy.
How will the $26 million be spent?
Cambridge Enterprise reports the raise funds a five-fold increase in team size and expansion from cement into steel, glass and chemicals. That sequencing is the standard Series A playbook: prove the product in one vertical with lighthouse customers, then generalize the platform to adjacent processes with similar physics and similar economics. Founded in 2020 as Carbon Re and led by CEO Josh Vernon, the company spent its first years building the simulation and control stack before renaming for the scale of the emissions target.
Why does an industrial AI round matter now?
Energy prices and emissions regulation have turned plant efficiency into a software market, and investors are pricing accordingly. Plural leading a $26 million round into control software, rather than another consumer AI application, signals where applied-AI returns are being documented: heavy industry has measurable fuel bills that software can shrink, and savings can be audited against metered data rather than argued from engagement metrics.
The company's deployment and per-plant savings claims remain company-claimed, and the expansion targets will test whether cement-tuned control generalizes to furnaces and reactors with different dynamics. The round structure itself, a syndicate of impact and university funds alongside a venture lead, matches the dual return profile the company promises: margin and emissions from the same control loop.
