A London-based startup called Applied Computing wants to give oil and gas operators something they’ve never had: a single AI model that can see the entire plant at once. The company just closed a $20 million Series A round led by engineering giant KBR, with Databricks Ventures also chipping in. Founded in 2023, Applied Computing targets the messy data environment inside refineries and petrochemical facilities, where thousands of sensors track temperature, pressure, flow, and viscosity around the clock.

The problem, according to co-founder and CEO Callum Adamson, is that operators currently make decisions using less than 8% of the data they collect. The rest sits in silos—sensor readings, engineering docs, and physics models that rarely talk to each other in real time. Applied Computing’s foundation model, Orbital, combines a time-series model, a physics-based model, and a language model to predict what’s happening across a facility. It can flag anomalies, trace their root cause, and simulate how a proposed fix might ripple through the plant—all within minutes. Adamson says investigations that used to take days or weeks now take seconds.

The startup claims it has already gone from stealth to double-digit millions in annual recurring revenue in under 18 months. Orbital is deployed at unnamed large public oil and gas companies, and partners include Wipro and KBR, which has woven Orbital into its INSITE 3.0 platform for ammonia production. Applied Computing is also working with a major U.S. upstream operator and expects to announce a partnership with a European oil major soon. The company plans to use the fresh capital to expand internationally, hire AI researchers and engineers, and open a new office in Houston—adding to its London headquarters and Bengaluru hub. Adamson insists the real moat isn’t access to industrial data, but the ability to recruit top AI talent. His pitch: “If you’re a tier-one AI researcher, where are you going to work? I don’t think Shell’s on that list.”

Source: TechCrunch