Applied Computing wants to give oil and gas operators an AI model for

London-based startup Applied Computing has successfully closed a $20 million Series A funding round, led by engineering giant KBR with participation from Databricks Ventures. The company, founded in 2023, is developing a pioneering foundation AI model named Orbital, specifically tailored for the complex operations of the oil, gas, and petrochemical sectors. This significant investment aims to revolutionize how energy facilities manage and analyze their vast datasets.

Orbital addresses a critical challenge within the energy industry: the fragmented nature of operational data. Despite facilities collecting extensive information from thousands of sensors measuring parameters like temperature, pressure, and viscosity, operators typically utilize less than 8% of this available data for critical decision-making. The sheer volume and diversity of data sources – including sensor readings, engineering documentation, and intricate physics and chemistry models – make real-time analysis incredibly difficult.

Applied Computing co-founder and CEO Callum Adamson highlighted that the core issue isn't a lack of data, but rather the inability to quickly integrate these disparate sources. "It's getting those three data sources to talk to each other in real time. That's the real key," Adamson told TechCrunch. This integration challenge has traditionally led to time-consuming investigations and suboptimal operational efficiency.

Unlike conventional large language models focused on predicting text, Orbital employs a sophisticated hybrid approach. It integrates a time series model, a physics-based model, and a language model to accurately predict the state of an entire facility. This allows it to interpret sensor data while simultaneously considering the underlying physics, chemistry, equipment limitations, and human operational activities within a plant.

Furthermore, Orbital empowers technicians to conduct rapid simulations, modeling the potential downstream effects of a change in one part of a facility on its overall operations. Applied Computing asserts that this technology dramatically accelerates the identification and resolution of anomalies, condensing investigations that previously took days or weeks into mere seconds. The ultimate goal is to help operators minimize energy consumption and maintain optimal output levels.

The startup's innovative solution has already garnered significant market traction, moving from stealth mode to 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, as well as 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 and uses it for ammonia production. Applied Computing is also collaborating with a major U.S. upstream operator and anticipates announcing a partnership with a prominent European oil major soon.

Applied Computing is entering a competitive landscape populated by established industrial software providers like AspenTech and AVEVA, which offer simulation and modeling tools, as well as specialized AI startups such as Cognite and Seeq, focused on industrial data analysis. However, Adamson believes the company's primary differentiator lies in its ability to attract top-tier AI researchers to build a sophisticated model like Orbital. He posits that it is fundamentally an "AI problem," not solely a data or energy challenge, and that premier AI talent is drawn to cutting-edge research opportunities.

The KBR partnership also provides a strategic advantage, granting Applied Computing access to valuable operational data and industry expertise, alongside introductions to new potential clients. Adamson emphasized that real operational data from energy facilities is critical and cannot be fully replicated by simulated data.

Looking ahead, Applied Computing plans to leverage its $20 million Series A funding to fuel international expansion, recruit additional research and engineering talent, and pursue further deployments with energy clients globally. The company recently opened an office in Houston to better serve its North American customers and is actively planning an expansion into the Middle East, signaling an aggressive push into key energy markets worldwide.

FAQ

Q: What is Orbital and what problem does it solve for the energy industry?

A: Orbital is Applied Computing's foundation AI model designed for oil, gas, and petrochemical facilities. It addresses the challenge of data fragmentation by integrating sensor readings, engineering documentation, and physics/chemistry models to provide real-time operational insights, allowing operators to make faster, more informed decisions and improve efficiency.

Q: How does Orbital differentiate itself from existing industrial software solutions?

A: Orbital distinguishes itself by combining a time series model, a physics-based model, and a language model to predict facility states and run simulations with unprecedented speed. Applied Computing's CEO Callum Adamson also highlights the company's focus on attracting top-tier AI research talent as a key competitive advantage, rather than just data or energy expertise.

Q: How will Applied Computing utilize its recent $20 million Series A funding?

A: The funding will be used to support the company's international expansion, recruit more research and engineering personnel, and pursue additional deployments with energy clients. This includes opening a new office in Houston and planning an expansion into the Middle East.