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Applied Computing raises £14.8m to scale AI for energy operators

Applied Computing, the UK AI firm building foundation AI for energy operators, has closed a $20m (£14.8m) funding round and announced its expansion into the United States with the opening of a new office in Houston, Texas. Applied Computing’s flagship platform, Orbital, is the first foundation model built specifically for

  • Kirstie Pickering
  • July 16, 2026
  • 0 Comments

Applied Computing, the UK AI firm building foundation AI for energy operators, has closed a $20m (£14.8m) funding round and announced its expansion into the United States with the opening of a new office in Houston, Texas.

Applied Computing’s flagship platform, Orbital, is the first foundation model built specifically for energy operations, combining physics-grounded intelligence with models across chemical engineering, time-series forecasting and language.

Orbital is designed to help operators improve efficiency, reduce emissions, strengthen reliability and make better decisions.

The opening of the Houston office marks the company’s formal entry into the US market and will support deeper engagement with customers and partners across North America.

The new funding will support Applied Computing’s continued international expansion, accelerate commercial deployment with global energy operators, and deepen investment in its AI research organisation.

The round was led by KBR with participation from Databricks Ventures. KBR and Applied Computing have also entered into a multi-year agreement to deliver exclusive AI products for the energy sector.

“It’s our mission to provide operators with a foundation model that unlocks advantages at scale while delivering pathways to production that are safer, more efficient and far less carbon intensive,” says Callum Adamson, CEO and co-founder of Applied Computing. 

“KBR is a natural partner for that mission. Their decades of data, industry domain knowledge and global reach mean we can now accelerate deployment of Orbital across the sector.”

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