Applied Computing's AI Model Aims to Revolutionize Oil and Gas Operations

Key points

• Applied Computing, a London-based startup founded in 2023, raised $20 million in Series A funding led by KBR, with Databricks Ventures also participating.
• The company built Orbital, a foundation AI model for oil, gas, and petrochemical industries.
• Orbital combines sensor readings with physics and chemistry models to predict facility states and run simulations.
• Applied Computing reached double-digit millions in annual recurring revenue within 18 months of leaving stealth.
• The company has opened a Houston office and is eyeing Middle East expansion.

A London startup called Applied Computing has raised $20 million, led by engineering firm KBR with Databricks Ventures joining in, to keep building Orbital, its AI model for energy facilities.

How does Orbital work?

Orbital is a foundation AI model, meaning it fuses three distinct model types: a time-series model that reads sensor streams, a physics-based model that understands how pressure and temperature behave, and a language model that interprets engineering documents. That combination lets it predict a facility's current state and model what happens if an operator changes something upstream.

CEO Callum Adamson told TechCrunch that large facilities typically use less than 8% of their available data because sensor readings, engineering documents, and physics knowledge are hard to combine quickly. Orbital is built to close that gap in real time.

Speed is the pitch. Adamson claims the product can compress investigations that once took days into seconds, flagging anomalies, tracing their causes, and modelling whether a proposed fix might cause trouble elsewhere.

What has it achieved so far?

The startup reached double-digit millions in annual recurring revenue within 18 months of leaving stealth. Customers include large, publicly listed upstream and downstream energy companies, though Adamson declined to name a count. Partners include Indian energy firm Wipro and KBR itself, which has folded Orbital into its INSITE 3.0 platform for ammonia production. A partnership with a European oil major was said to be weeks away from announcement.

This is the first time we've reported on an oil-and-gas-focused AI model raising at this scale, and the KBR angle is worth watching: the engineering giant isn't just a backer but a distribution channel, giving Applied Computing introductions to potential customers alongside operational data.

What's next for Applied Computing?

With a new Houston office added to existing bases in London and Bengaluru, the company is closer to two North American customers already using Orbital. The $20 million will fund international growth, research hires, and new energy-sector deployments. Middle East expansion is also planned.

Should you worry about the competition?

Applied Computing faces established names like AspenTech and AVEVA on simulation software, plus AI-focused rivals Cognite and Seeq on the data analytics side. Adamson's counter is blunt: he argues the real barrier to copying Orbital is assembling top AI researchers, not acquiring data or domain knowledge. "It's an AI problem. It's not a data problem, and it's not an energy problem," he told TechCrunch.

Operational refinery data isn't publicly available, which gives Orbital's training set a structural advantage that a new entrant would struggle to replicate quickly. That moat is real, but it only holds if Applied Computing keeps signing customers before a better-funded competitor decides the market is worth entering.