Applied Computing wants to give oil and gas operators an AI model for the entire plant
Applied Computing, a London-based startup, has raised $20 million to build a foundation AI model for the oil, gas, and petrochemical industry. The model, called Orbital, combines a time series model, a physics-based model, and a language model to predict the state of a fa…
Intelligence analysis by Llama
Applied Computing has developed an AI model called Orbital that can help oil and gas operators make faster and more accurate decisions. The model combines different types of data and can identify potential problems before they occur. The startup has raised $20 million in funding and is working with several major energy companies.
Imagine you're working at a big oil refinery, and you need to fix a problem with one of the machines. But if you fix it the wrong way, it could cause problems elsewhere in the refinery. Applied Computing's AI model, Orbital, can help you figure out the best way to fix the problem, so you can avoid causing more problems. It's like having a super-smart assistant who can help you make faster and more accurate decisions.
Analysis
A $60B Vote of Confidence
Applied Computing's $20 million Series A funding round is a significant vote of confidence in the startup's AI model for the oil, gas, and petrochemical industry. The funding was led by engineering giant KBR, with Databricks Ventures participating. This investment demonstrates the potential of Applied Computing's technology to transform the industry.
Why Cursor?
Applied Computing's AI model, Orbital, is designed to help oil and gas operators make faster and more accurate decisions. The model combines a time series model, a physics-based model, and a language model to predict the state of a facility. It can flag anomalies, investigate their causes, and model whether a proposed fix could create problems elsewhere in the facility, all within minutes. This is a significant improvement over current methods, which often rely on manual analysis and can take days or weeks to complete.
The Road Ahead
Applied Computing plans to use the funding to expand internationally, hire for research and engineering roles, and explore deployments with energy clients. The company has already opened an office in Houston and is working with several major energy companies, including Wipro and KBR. With its AI model and growing partnerships, Applied Computing is well-positioned to transform the oil and gas industry.
Key points
- Applied Computing has raised $20 million in funding to build a foundation AI model for the oil, gas, and petrochemical industry.
- The model, called Orbital, combines a time series model, a physics-based model, and a language model to predict the state of a facility.
- Orbital can flag anomalies, investigate their causes, and model whether a proposed fix could create problems elsewhere in the facility, all within minutes.
- Applied Computing is working with several major energy companies, including Wipro and KBR.
- The company plans to use the funding to expand internationally, hire for research and engineering roles, and explore deployments with energy clients.
If Applied Computing's AI model is successful, it could lead to significant improvements in the efficiency and safety of the oil and gas industry. The model could help operators reduce energy use, maintain output, and make more informed decisions. This could have a positive impact on the environment and the economy.
However, there are also potential risks associated with the adoption of Applied Computing's AI model. For example, if the model is not accurate or reliable, it could lead to incorrect decisions and potentially harm the environment or the economy. Additionally, the model may not be compatible with existing systems or infrastructure, which could create technical challenges and delays.
