London AI Startup Raises $20M to Help Oil and Gas Plants Finally Use Their Own Data

A London-based startup called Applied Computing has raised $20 million in Series A funding to tackle a stubborn problem in the energy industry: plants that run on less than 8% of the data they collect. The round was led by engineering giant KBR, with Databricks Ventures also participating. The company, founded in 2023, is building a foundation AI model for oil, gas, refining, and petrochemical facilities - places where thousands of sensors track everything from temperature to viscosity, but where that data rarely gets fully used.

The startup's model, named Orbital, combines time-series analysis, physics-based modeling, and language processing to predict what's happening in a facility in real time. Co-founder and CEO Callum Adamson says the core challenge is getting sensor readings, engineering documents, and physics principles to talk to each other fast enough. Orbital can flag an anomaly, trace its cause, and simulate a fix - all in minutes. Adamson claims the tool compresses investigations that used to take days or weeks into seconds, helping operators cut energy use without losing output.

Applied Computing says it has already reached double-digit millions in annual recurring revenue in under 18 months. Customers include large publicly traded upstream and downstream energy companies, though the startup won't name most of them yet. Partners include Indian energy firm Wipro and KBR, which has integrated Orbital into its INSITE 3.0 platform for ammonia production. The company is also working with a major U.S. upstream operator and expects to announce a partnership with a European oil major soon. With the new funding, Applied Computing plans to expand internationally, hire more researchers and engineers, and explore deployments in the Middle East. It has also opened a Houston office to get closer to North American customers.

Source: TechCrunch