Applied Computing, a startup based in London, is making strides in the oil, gas, and petrochemical sector by developing a foundational AI model aimed at improving data management in these industries. The company has successfully secured $20 million in Series A funding, led by renowned engineering firm KBR, with participation from Databricks Ventures.
Established in 2023, Applied Computing focuses on the complex data landscape of oil, gas, refining, and petrochemical operations, where a single facility may incorporate thousands of sensors that monitor variables such as temperature, pressure, velocity, and viscosity. The vast potential for enhancing data tracking in the energy sector faces challenges due to significant fragmentation.
As a result, operators often rely on less than 8% of the data at their disposal when making operational decisions, according to Callum Adamson, co-founder and CEO of Applied Computing. He explains that while the necessary data is often collected, facilities struggle to effectively integrate sensor data, engineering documentation, and the principles of physics and chemistry in a timely manner for predictive analytics.
Adamson emphasizes the importance of real-time communication among these data sources, stating that this integration is crucial for effective decision-making.
Rather than relying on conventional large language models that predict the next word, Applied Computing's model, named Orbital, employs a combination of a time series model, a physics-based model, and a language model to forecast a facility's operational state. Orbital synthesizes sensor data while considering physical and chemical constraints of the equipment and the activities of operators. This model also enables technicians to simulate the effects of modifications in one part of a facility on its entire operation.
In essence, Applied Computing is delivering rapid solutions; Orbital is touted to identify anomalies, analyze the causes, and simulate the impact of adjustments within minutes. Adamson notes that investigations, which would typically take days or weeks, can now be condensed to mere seconds, thereby helping operators minimize energy consumption and sustain production levels.
This value proposition of speed has resonated well with the market. According to the company, it has transitioned from a stealth mode to achieving double-digit millions in annual recurring revenue in less than 18 months. While Adamson mentions that Orbital is already in use by several well-established upstream oil and gas, along with downstream refining and petrochemical firms, he refrains from disclosing specific customer numbers.
Among the company's collaborators is Wipro, an Indian energy firm, and KBR, which has incorporated Orbital into its INSITE 3.0 digital platform for energy initiatives, notably for ammonia production. Moreover, Applied Computing is planning to announce a partnership with a significant European oil company and is currently engaging with a major U.S. upstream operator.
Nonetheless, Applied Computing is entering a competitive environment filled with established industrial software providers and niche AI startups. Competitors like AspenTech offer simulation and AI modeling tools while AVEVA provides solutions for physics-based process simulation and “what-if” analysis for industrial facilities. Other companies such as Cognite and Seeq focus on the data aspect, helping facilities analyze industrial data and implement AI-driven workflows.
Adamson contends that the company's distinct advantage lies not in accessing industrial data or process knowledge but rather in its ability to assemble top-tier AI researchers to develop a model that competes effectively with Orbital.
“It’s an AI challenge, not merely a data or energy issue,” he states. “If you're a leading AI researcher, companies like Shell might not be at the top of your list for where to work.”
He also highlights that Orbital benefits from the operational data it accesses through its deployments, noting that data from refinery operations is generally not publicly available and that simulated data does not accurately depict the complexities of functioning plants.
Additionally, the partnership with KBR is expected to enhance Applied Computing's capabilities by providing operational data, industry insights, and openings to potential new clients.
The startup intends to utilize the $20 million to further its international expansion, recruit for research and development roles, and explore additional deployments with energy industry clients. Recently, Applied Computing announced the establishment of a new office in Houston, adding to its headquarters in London and its operational hub in Bengaluru. Adamson indicates that this U.S. location will position the company close to two existing clients in North America, with plans for an expansion into the Middle East also underway.
