Applied Computing Secures $20 Million to Revolutionize Oil and Gas Operations with AI

Washington DC, United States Jul 16, 2026 ALN: Applied Computing, a London-based startup focused on creating a foundational AI model for the oil, gas, and petrochemical industry, has successfully raised $20 million in a Series A funding round led by engineering giant KBR, with participation from Databricks Ventures.

Founded in 2023, Applied Computing aims to tackle the complexities of oil, gas, refining, and petrochemical systems, where individual facilities can have thousands of sensors measuring various parameters such as temperature, pressure, velocity, and viscosity. Despite the vast amount of data available, facilities often make operational decisions based on less than 8% of this data, according to co-founder and CEO Callum Adamson. He noted that while operators collect significant information, they struggle to integrate sensor readings, engineering documentation, and relevant physics and chemistry data quickly enough for effective analysis and predictions.

The oil and gas industry has long been characterized by its reliance on data-driven decision-making; however, the sheer volume of data generated by modern facilities can be overwhelming. Traditional approaches often result in missed opportunities for optimization and efficiency. Adamson highlighted that the challenges faced by operators stem from the inability to effectively synthesize and analyze data from disparate sources. "The key is getting those three data sources to communicate in real time," Adamson explained. This need for integration underscores the broader trend in industrial sectors towards more sophisticated data analytics and AI solutions.

Unlike traditional large language models that predict the next word, Applied Computing's foundation model, Orbital, combines a time series model, a physics-based model, and a language model to predict the state of a facility. This innovative approach allows for real-time analysis of sensor data while considering the physical and chemical constraints of equipment and operator activities. By leveraging advanced modeling techniques, Orbital can simulate how changes in one part of a facility could impact overall operations, potentially transforming the way operators approach maintenance and optimization.

Applied Computing emphasizes speed as a core advantage. The company claims that Orbital can identify anomalies, investigate their causes, and model potential fixes within minutes, compressing investigations that previously took days or weeks into mere seconds. This capability not only aids in reducing energy consumption but also helps maintain operational output, which is crucial in an industry where even minor inefficiencies can lead to substantial financial losses. The ability to rapidly respond to operational challenges can enhance a company's competitiveness in a market that is increasingly focused on sustainability and efficiency.

The startup's rapid growth is evident, having transitioned from stealth mode to achieving double-digit millions in annual recurring revenue in under 18 months. Adamson revealed that Orbital is currently utilized by several large, publicly listed companies in the upstream oil and gas, downstream refining, and petrochemical sectors, although he did not disclose the exact number of customers. This growth trajectory reflects a broader trend of increasing investment in AI technologies within the energy sector, as companies seek to leverage data to drive operational improvements.

Partnerships with companies like Indian energy firm Wipro and KBR, which has integrated Orbital into its INSITE 3.0 digital platform for energy projects, further bolster Applied Computing's position. The technology is being utilized for ammonia production, a critical component in the fertilizer industry, which is heavily reliant on efficient production processes. Adamson mentioned that the startup is collaborating with a major U.S. upstream operator and plans to announce a partnership with a European oil major soon, indicating a growing recognition of the value that AI can bring to traditional sectors.

However, Applied Computing faces competition from established industrial software providers and specialized AI startups. Companies like AspenTech offer simulation and AI-powered modeling software for various operations, while AVEVA specializes in physics-based process simulation and optimization. Other firms, such as Cognite and Seeq, focus on the data layer, helping facilities analyze industrial data and apply AI to streamline workflows. This competitive landscape underscores the importance of continuous innovation in AI technologies to maintain a leading position in the market.

Adamson contends that Applied Computing's competitive edge lies not in access to industrial data or process knowledge but in assembling a team of AI researchers capable of developing a model that can rival Orbital. He stated, "It’s an AI problem. It’s not a data problem, and it’s not an energy problem. If you’re a tier-one AI researcher, where are you going to work? I don’t think Shell’s on that list." This perspective highlights the evolving nature of talent acquisition in the tech industry, where attracting top-tier AI researchers is becoming increasingly critical for startups aiming to innovate.

The operational data Orbital receives through its deployments is typically not publicly available, and simulated data cannot fully replicate the dynamics of a functioning plant. The partnership with KBR is expected to enhance Applied Computing's access to operational data and industry expertise, facilitating introductions to potential customers. This collaboration reflects a growing trend of partnerships between tech startups and established industry players, which can provide the resources and credibility necessary for emerging companies to scale their solutions effectively.

The $20 million raised will be utilized to support international expansion, recruit for research and engineering roles, and explore further deployments with energy clients. Recently, the company announced the opening of an office in Houston, complementing its headquarters in London and operational hub in Bengaluru. Adamson indicated that the U.S. base positions the startup closer to two existing customers in North America, with plans for expansion into the Middle East also underway. This strategic expansion reflects the increasing demand for AI-driven solutions in the global energy market, as companies seek to enhance efficiency and sustainability in their operations.

In conclusion, Applied Computing's innovative approach to integrating AI into the oil and gas sector represents a significant step forward in harnessing the power of data analytics for operational efficiency. As the industry continues to grapple with the complexities of modern energy production and environmental sustainability, solutions like Orbital could play a pivotal role in shaping the future of oil, gas, and petrochemical operations. The successful funding round and rapid growth trajectory of Applied Computing signal a promising future for AI technologies in the energy sector, potentially leading to transformative changes in how companies operate and make decisions in the face of an evolving market landscape.