Applied Computing wants to give oil and gas operators an AI model for the entire plant
Applied Computing has raised a $20M Series A to build a foundation AI model for the oil, gas and petrochemical industry. Applied Computing , a London-based startup that's building a foundation AI model for the oil, gas, and petrochemical industry, has raised a $20 million Series A led by engineering giant KBR, with Databricks Ventures participating. Founded in 2023, the startup targets oil, gas, refining, and petrochemical systems, where a single facility can have thousands of sensors measuring everything from temperature and pressure to velocity and viscosity.
Key Takeaways
- While there's a huge market for helping energy companies solve the data-tracking problem, the fragmentation presents a significant hurdle.
Facilities consequently make operating decisions using less than 8% of the data available to them, says Applied Computing's co-founder and CEO Callum Adamson (pictured above, right).
- It does this by analyzing sensor readings, keeping physics and chemistry in mind, and recognizing a facility's equipment constraints and operator activity.
It also allows technicians to run simulations of how a change in one part of a facility could affect the rest of its operations.
- Its partners include Indian energy company Wipro, and KBR, which has integrated Orbital into its INSITE 3.
0 digital platform for energy projects, and is using the product for ammonia production.
- Cognite and Seeq target the data layer, helping facilities analyze industrial data, and apply AI to design workflows.
Adamson argues that the company's moat is not access to industrial data or process knowledge, but rather assembling AI researchers to build a model that can compete with Orbital.
- The KBR partnership may help the company, too.
Stats & Key Facts
- #Applied Computing has raised a $20M Series A to build a foundation AI model for the oil, gas and petrochemical industry.
- #Applied Computing has raised a $20M Series A to build a foundation AI model for the oil, gas and petrochemical industry.
- #Applied Computing , a London-based startup that's building a foundation AI model for the oil, gas, and petrochemical industry, has raised a $20 million Series A led by engineering giant KBR, with Databricks Ventures participating.
- #The startup says it has gone from stealth to double-digit millions in annual recurring revenue in under 18 months.
While there's a huge market for helping energy companies solve the data-tracking problem, the fragmentation presents a significant hurdle. Facilities consequently make operating decisions using less than 8% of the data available to them, says Applied Computing's co-founder and CEO Callum Adamson (pictured above, right). Operators already collect much of this information, he said, but they struggle to combine the sensor readings, engineering documentation, and physics and chemistry quickly enough to analyze and make predictions.
"It's getting those three data sources to talk to each other in real time. That's the real key," he told TechCrunch. Unlike large language models, which predict the next word, Applied Computing says its foundation model, Orbital, combines a time series model, a physics-based model, and a language model to predict the state of a facility.
It does this by analyzing sensor readings, keeping physics and chemistry in mind, and recognizing a facility's equipment constraints and operator activity. It also allows technicians to run simulations of how a change in one part of a facility could affect the rest of its operations. Essentially, Applied Computing is pitching speed: It claims Orbital can flag anomalies, investigate what caused them, and model whether a proposed fix could create problems elsewhere in the facility, all within minutes.
For more details please read the original article at TechCrunch AI.
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