Applied Computing Raises $20M to Build Foundation AI Model for Oil and Gas Industry

Applied Computing Secures Series A Funding to Transform Industrial Operations

Applied Computing, a London-based startup founded in 2023, has raised $20 million in Series A funding led by engineering giant KBR, with Databricks Ventures participating1

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. The company is building a foundation AI model specifically designed for the oil and gas sector, targeting refining and petrochemical facilities where thousands of sensors generate vast amounts of data that largely goes unused. Co-founder and CEO Callum Adamson revealed that facilities currently make operating decisions using less than 8% of available data, despite already collecting extensive information from sensors measuring temperature, pressure, velocity, and viscosity1

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The Orbital Foundation Model Combines Multiple AI Approaches

Unlike traditional large language models, the Orbital foundation model fuses three distinct components: a time-series data model, physics-based modeling, and language processing capabilities2

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. This hybrid architecture allows Orbital to predict facility states by analyzing sensor readings while accounting for chemistry, equipment constraints, and operator activity. The core challenge, according to Adamson, is not data collection but data fragmentation—getting sensor readings, engineering documentation, and the underlying physics and chemistry to communicate in real time1

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. Technicians can also run simulations to understand how changes in one section of a facility might affect operations elsewhere, a capability that historically required consultants and extended downtime.

Speed and Real Time Anomaly Detection Drive Value Proposition

The startup's primary pitch centers on speed to optimize refinery operations. Applied Computing claims Orbital can flag anomalies, investigate their causes, and model whether proposed fixes might create problems elsewhere—all within minutes1

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. Adamson asserts the product compresses investigations that previously took days or weeks into seconds, enabling operators to reduce energy consumption while maintaining output. This real time anomaly detection capability addresses a critical pain point in industrial operations where delayed responses can result in significant financial and operational consequences.

Rapid Revenue Growth and Strategic Partnerships

The company reports reaching double-digit millions in annual recurring revenue within 18 months of emerging from stealth1

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. While Adamson declined to specify customer numbers, he confirmed Orbital is deployed at "large, publicly listed" upstream oil and gas, downstream refining, and petrochemicals companies2

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. Strategic partnerships include Indian energy company Wipro and KBR, which has integrated Orbital into its INSITE 3.0 digital platform for energy projects and is using it for ammonia production1

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. The startup is also working with a major US upstream operator and plans to announce a partnership with a European oil major in coming weeks.

Competing Against Entrenched Industrial Software Giants

Applied Computing enters a market dominated by established players including AspenTech, which sells simulation and AI-powered modeling software for upstream, refining, and chemical operations, and AVEVA, which offers physics-based process simulation and what-if modeling1

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. Data-layer specialists Cognite and Seeq also compete in this space. Adamson argues the company's competitive advantage lies not in access to industrial data or process knowledge, but in assembling top-tier AI researchers capable of building models that can compete with Orbital. "It's an AI problem. It's not a data problem, and it's not an energy problem," he told TechCrunch, adding that tier-one AI researchers are unlikely to choose traditional energy companies as employers1

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Expansion Plans and Access to Proprietary Operational Data

Applied Computing will use the $20 million to expand internationally, hire research and engineering talent, and explore new deployments with energy clients1

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. The company opened a Houston office to complement its London headquarters and Bengaluru operational hub, positioning itself closer to North American customers, with Middle East expansion planned1

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. Adamson emphasizes that operational data from working refineries is not publicly available, and simulated data cannot fully reproduce real-world plant conditions, making each deployment a valuable data asset2

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. The KBR partnership provides access to operational data, industry expertise, and customer introductions—resources that could prove decisive in a market where established competitors hold significant installed bases.