Applied Computing, a London-based startup focused on developing a foundational AI model for the oil, gas, and petrochemical industries, has successfully raised $20 million in a Series A funding round. The investment was led by engineering giant KBR, with Databricks Ventures also participating. Founded in 2023, the company aims to tackle the complex data challenges inherent in large-scale energy facilities, which often feature thousands of sensors monitoring everything from temperature and pressure to velocity and viscosity.

Despite the immense volume of data collected, energy companies frequently make operational decisions utilizing less than 8% of the available information. Callum Adamson, co-founder and CEO of Applied Computing, highlights that operators struggle to rapidly integrate sensor readings, engineering documentation, and complex physics and chemistry principles to enable real-time analysis and predictive capabilities. To address this, Applied Computing developed Orbital, a unique foundation model that combines time series, physics-based, and language models. Unlike conventional large language models, Orbital predicts the state of a facility by analyzing sensor data, adhering to physical and chemical laws, and understanding equipment constraints and operator actions. It also empowers technicians to run simulations, modeling how changes in one part of a facility could impact overall operations.

Orbital’s primary advantage lies in its speed. Applied Computing asserts that its platform can identify anomalies, determine their root causes, and simulate the effects of proposed solutions across a facility within minutes. This capability significantly compresses investigation times that previously spanned days or weeks into mere seconds, enabling operators to optimize energy consumption and sustain output. The startup has demonstrated rapid growth, achieving double-digit millions in annual recurring revenue in under 18 months. Orbital is currently deployed at several large, publicly listed upstream oil and gas, downstream refining, and petrochemical companies. Key partnerships include Indian energy firm Wipro and KBR, which has integrated Orbital into its INSITE 3.0 digital platform for energy projects, specifically utilizing it for ammonia production. The company is also collaborating with a major U.S. upstream operator and plans to announce a partnership with a European oil major soon.

Applied Computing operates in a competitive landscape, facing established industrial software providers like AspenTech and AVEVA, as well as specialized AI startups such as Cognite and Seeq. However, Adamson contends that the company’s competitive edge is not merely access to industrial data or process knowledge, but rather its ability to attract and assemble top-tier AI researchers capable of building a model as sophisticated as Orbital. He emphasizes that the core challenge is an AI problem, not solely a data or energy problem. Furthermore, the operational data Orbital gathers through its deployments, combined with strategic partnerships like that with KBR, provides invaluable real-world insights and industry expertise, which simulated data cannot fully replicate.

The $20 million funding will fuel Applied Computing’s international expansion, support the hiring of additional research and engineering talent, and facilitate new client deployments. The company recently opened an office in Houston, complementing its London headquarters and Bengaluru operational hub, to better serve existing North American clients. Plans for expansion into the Middle East are also underway.

Key Takeaways

• Applied Computing secured $20 million in Series A funding, led by KBR, to advance its AI foundation model for the oil, gas, and petrochemical industries.
• Its Orbital model leverages AI to analyze vast industrial data in real-time, enabling operators to make faster, more informed decisions, reduce energy use, and maintain output.
• The startup has achieved significant early traction, including double-digit millions in annual recurring revenue and strategic partnerships, despite a competitive market.

Editor’s Analysis & Impact

This significant investment in Applied Computing underscores the accelerating digital transformation within the traditional energy sector. The ability to harness AI for real-time operational insights addresses a critical industry pain point: the underutilization of vast sensor data. If Orbital proves scalable and effective, it could substantially enhance efficiency, reduce operational costs, and improve safety across oil, gas, and petrochemical facilities. The strategic partnership with KBR not only provides capital but also crucial industry expertise and access to proprietary operational data, strengthening Applied Computing’s competitive moat against established industrial software giants and other AI startups. This trend suggests a broader shift towards AI-driven predictive maintenance and optimization, potentially setting new industry standards for operational intelligence and sustainability.

Frequently Asked Questions

Q: What is Applied Computing's core offering?
A: Applied Computing provides an AI foundation model called Orbital, designed for the oil, gas, and petrochemical industries. It integrates time series, physics-based, and language models to predict the state of industrial facilities in real-time.

Q: How does Orbital benefit energy operators?
A: Orbital helps operators make faster, more informed decisions by quickly analyzing complex data, flagging anomalies, investigating causes, and simulating potential fixes. This can lead to reduced energy consumption, improved operational efficiency, and maintained output.

Q: Who are Applied Computing's key investors and partners?
A: The company's $20 million Series A round was led by engineering giant KBR, with participation from Databricks Ventures. Key partners include KBR, which has integrated Orbital into its digital platform, and Indian energy company Wipro.