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You are at:Home»AI»Applied Computing wants to give oil and gas operators an artificial intelligence model for the entire plant
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Applied Computing wants to give oil and gas operators an artificial intelligence model for the entire plant

techtost.comBy techtost.com16 July 202604 Mins Read
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Applied Computinga London-based startup building a foundational AI model for the oil, gas and petrochemical industry has raised a $20 million Series A round led by engineering giant KBR, with participation from Databricks Ventures.

Founded in 2023, the startup is targeting oil, gas, refining and petrochemical systems, where a unit can have thousands of sensors that measure everything from temperature and pressure to velocity and viscosity. While there is one huge market to help energy companies solve the data tracking problem, fragmentation which presents a major obstacle.

As a result, facilities are making operational decisions using less than 8% of the data available to them, says Applied Computing co-founder and CEO Callum Adamson (pictured above, right). Operators already collect much of this information, he said, but struggle to combine sensor readings, technical documentation, and physics and chemistry quickly enough to analyze and make predictions.

“These three data sources are talking to each other in real time. That’s the real key,” he told TechCrunch.

Unlike big language models, which predict the next word, Applied Computing says its foundational model, Orbital, combines a time series model, a physics-based model and a language model to predict the state of a facility. It does this by analyzing sensor readings, considering physics and chemistry, and recognizing a facility’s equipment limitations and operator activity. It also allows technicians to run simulations of how a change in one part of a facility could affect the rest of its operations.

Image Credits:Applied Computing / Applied Computing

Essentially, Applied Computing delivers speed: It claims Orbital can pinpoint anomalies, investigate what caused them, and model whether a proposed fix could cause problems elsewhere in the facility, all within minutes. Adamson claims the product can compress surveys that previously took days or weeks into seconds, helping operators reduce energy use and maintain production.

This promise of speed seems to have found believers. The startup says it has gone from stealth to double-digit million annual recurring revenue in less than 18 months. Adamson said Orbital is used by some “large, publicly traded” oil and gas, downstream refining and petrochemical companies, though he declined to say how many customers it has.

Its partners include Indian energy company Wipro and KBR, which has integrated Orbital into its INSITE 3.0 digital platform for energy projects and uses the product to produce ammonia. Adamson said the startup is also working with a “major U.S. upstream company” and plans to announce a partnership with a European oil major in the coming weeks.

However, Applied Computing is entering a market that has established industrial software vendors as well as more focused AI startups. AspenTech sells AI-powered simulation and modeling software for upstream, refining and chemical operations, while ABEBA offers physics-based process simulation, optimization and “what-if” modeling for industrial facilities. Cognite and See target the data layer, helping facilities analyze industrial data and apply artificial intelligence to workflow design.

Adamson argues that the company’s moat is not access to industrial data or process knowledge, but to bring together AI researchers to build a model that can compete with Orbital.

“It’s an AI problem. It’s not a data problem and it’s not an energy problem,” he said. “If you’re a top-tier AI researcher, where will you work?… I don’t think Shell is on that list.”

Adamson also showed the data Orbital receives through its deployments. Operational data from refineries and other energy facilities is generally not publicly available, he said, and simulated data cannot fully replicate what happens inside a working plant.

KBR’s partnership can also help the company. Adamson said the partnership gives Applied Computing access to operational data, industry expertise and also introductions to more potential customers.

Applied Computing plans to use the $20 million to expand internationally, hire research and engineering roles and explore facilities with energy customers.

The company announced Thursday that it has also opened an office in Houston, adding to its London headquarters and operations hub in Bangalore. Adamson said the US base brings the startup closer to two existing customers in North America, and an expansion to the Middle East is also in the works.

When you purchase through links in our articles, we may earn a small commission. This does not affect our editorial independence.

Applied artificial computing energy entire gas give intelligence model oil oil and natural gas operators petrochemicals plant
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