The startup’s flagship product, Orbital, distinguishes itself from standard large language models by integrating time-series data, physics-based simulations, and traditional language processing. According to co-founder and CEO Callum Adamson, this allows the system to analyze equipment constraints and operator activities in real-time. By synthesizing these inputs, the platform can flag anomalies and model the impact of operational changes, potentially compressing investigations that previously spanned weeks into a matter of minutes.
In section Startups & Technology
Applied Computing secures $20 million to automate industrial plant AI
London-based startup Applied Computing has raised $20 million in a Series A round led by engineering giant KBR to scale its industrial AI platform. The company aims to solve the industry-wide data fragmentation problem that currently leaves energy operators utilizing less than 8% of their available facility sensor information.
Since exiting stealth 18 months ago, the company has secured double-digit millions in annual recurring revenue. Its technology is currently deployed by several large, publicly listed energy firms, with partners including Wipro and KBR, which has integrated Orbital into its INSITE 3.0 digital platform. While the firm faces competition from established players like AspenTech and AVEVA, Adamson contends that their primary advantage lies in their ability to attract top-tier AI research talent. The new funding will support international expansion, including the opening of a Houston office to better serve North American clients and facilitate planned growth into the Middle East.
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