Gigaton raises $26m Series A led by Plural
According to Sifted, London-based Gigaton has raised a $26 million Series A led by Plural, with reported participation from investors including 2150, Semapa Next, Planet A Ventures, Cambridge Enterprise Ventures, the UCL Technology Fund, and Clean Growth Fund. Multiple outlets report Gigaton, a UCL and Cambridge spinout formerly known as Carbon Re, builds AI control software for energy-intensive heavy industry, aiming to replace traditional industrial control systems in cement, steel, glass, and chemicals plants. Coverage notes the software is already deployed with producers reported to include Holcim, Heidelberg Materials, Adani Cement, and Mannok, and that Gigaton claims per-plant operational savings of $1 million to $3 million a year alongside emissions reductions. The company says it will use the funding to grow its team and expand beyond cement.
What happened
According to Sifted, London-based Gigaton has raised a $26 million Series A round led by investor Plural. Multiple outlets report participation from 2150, Semapa Next, and existing backers including Planet A Ventures, Cambridge Enterprise Ventures, the UCL Technology Fund, and Clean Growth Fund. Coverage identifies Gigaton as a UCL and Cambridge spinout, formerly known as Carbon Re, that uses AI to cut cost and energy consumption in manufacturing.
What the company does
Per reporting, Gigaton builds AI software intended to replace traditional control systems that run energy-intensive plants, starting with cement and extending to steel, glass, and chemicals. Outlets report the software is already deployed with producers including Holcim, Heidelberg Materials, Adani Cement, and Mannok, and that Gigaton claims operational savings of roughly $1 million to $3 million per plant per year, alongside site-level emissions reductions. The company says it will use the round to grow its team and expand beyond cement.
Why it matters
Class B analysis: startups addressing industrial energy and cost optimization typically combine physics-informed modeling, sensor-driven time-series forecasting, and closed-loop control that interfaces with programmable logic controllers and manufacturing execution systems. These stacks demand reliable streaming-telemetry feature engineering, domain-specific anomaly detection, and safety-constrained decision logic rather than open-ended generative models.
What to watch
- •Third-party validation of the reported energy and cost savings, and pilot-to-production conversion rates.
- •Integration complexity with legacy equipment and the quality of labeled operational data needed to validate models at scale.
- •Partnerships or standards work with original-equipment manufacturers and automation vendors as Gigaton expands across heavy-industry verticals.
Key Points
- 1Gigaton (formerly Carbon Re, a UCL and Cambridge spinout) raised a $26m Series A led by Plural to scale AI control software for heavy industry.
- 2The platform targets cement, steel, glass, and chemicals plants, with coverage reporting deployments at producers such as Holcim and Heidelberg Materials.
- 3Reported per-plant savings of $1-3 million a year plus emissions cuts illustrate the industrial-AI thesis: measurable operational ROI, contingent on integration with legacy control systems.
Scoring Rationale
A $26m Series A for an industrial-AI startup is a mid-tier funding event that is notable to practitioners tracking decarbonization and heavy-industry automation, especially given reported blue-chip deployments and a UCL and Cambridge pedigree. It is not a frontier-model or platform-changing release, which keeps it in the notable rather than major range.
Sources
Public references used for this report.
Practice interview problems based on real data
1,625 SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems
