Applied Computing raises $20M Series A to scale Orbital AI for oil and gas plants
Applied Computing raises $20M Series A led by KBR to scale Orbital, an AI model for oil and gas plants; expansion, hires and new Houston office planned.
Applied Computing, the London-based startup behind the Orbital foundation model, has closed a $20 million Series A round led by engineering firm KBR with participation from Databricks Ventures. The funding will accelerate deployment of Orbital, an AI platform the company says fuses time-series analytics, physics-based models and language models to monitor and predict the state of oil, gas and petrochemical facilities. Founded in 2023, Applied Computing aims to help operators use more of the data produced on plant floors and compress investigations that traditionally take days into minutes.
Series A details and investor signal
Applied Computing’s $20 million raise was led by KBR, with Databricks Ventures joining the round, reflecting growing interest from engineering and data infrastructure investors in industrial AI. Company leadership said the capital will support international expansion, engineering hires and wider customer deployments. The involvement of a major engineering contractor like KBR also provides commercial and operational channels that could accelerate adoption in complex industrial settings.
How Orbital combines models to predict plant behavior
Orbital is described by the company as a hybrid foundation model that integrates a time-series engine, physics-aware simulation and a natural language component to interpret engineering documentation. Rather than predicting text, the platform ingests streams of sensor data, maintenance logs and process diagrams and proposes probable causes and remediation steps when anomalies occur. The startup says these combined modalities let technicians simulate interventions and assess their downstream effects before applying changes on equipment.
Claims on speed, efficiency and data use
Applied Computing’s leadership says facilities typically act on less than 8% of available sensor data, and that Orbital is built to change that by making disparate data sources interoperable in real time. The company claims the platform can flag anomalies, run root-cause analysis and model corrective actions in minutes rather than days or weeks. Executives contend that compressing investigative cycles can reduce energy use, avoid production losses and improve operational resilience at scale.
Early traction and customer deployments
Since leaving stealth, the startup reports rapid revenue growth, reaching double-digit millions in annual recurring revenue in under 18 months. The company says Orbital is deployed at several large, publicly listed operators across upstream oil and gas, downstream refining and petrochemicals, though it declined to disclose customer counts. Applied Computing also noted work with a major U.S. upstream operator and signaled an imminent announcement with a European oil major.
Partnerships and integrations with industry players
Applied Computing has established partnerships intended to embed Orbital into established vendor ecosystems. KBR has integrated Orbital into its INSITE 3.0 digital platform and is using the model for ammonia production workflows. The startup also lists a relationship with Indian systems integrator Wipro, positioning Orbital as both a standalone product and a component within broader engineering and digital-transformation projects. Executives say these alliances provide operational data access and market introductions that are critical for scaling complex industrial deployments.
Competition and the company’s stated moat
The market for industrial digital twins, process simulation and data-layer analytics is crowded with legacy and specialized vendors such as AspenTech, AVEVA, Cognite and Seeq. Applied Computing argues its advantage lies in assembling AI research talent to build a model that can reason across sensors, physics and operator actions in real time. Company leadership has emphasized that proprietary operational data gathered through live deployments further refines the model in ways synthetic or public datasets cannot replicate.
Geographic expansion and hiring plans
Proceeds from the Series A will fund international expansion and additional hiring in research and engineering roles, the company said. Applied Computing has opened a Houston office to sit alongside its London headquarters and operational hub in Bengaluru, aiming to be closer to North American customers and to support planned growth in the Middle East. Leadership expects the U.S. presence to facilitate partnerships and faster onboarding of large industrial accounts.
Applied Computing’s announcement illustrates a broader industry push to apply advanced AI techniques to heavy industry, where the potential efficiency and safety gains can be significant but integration challenges remain. The company’s next steps—scaling deployments, proving outcomes on more live assets and competing against entrenched software suppliers—will be watched closely by operators and engineering partners seeking faster, data-driven operational decisions.
