McLaren Applied


We deliver extraordinary performance to the world by creating digital twins of complex physical assets and operational systems, which give us an unlimited ability to optimise real-world performance.

Our goal is to create digital twins that reflect the physical situation so accurately and robustly that they become inherently trusted as the master of the real – the digital master; directing, coordinating and supporting humans to make better decisions, faster, and deliver extraordinary levels of speed, efficiency and performance.

By deriving detailed insight on people, assets and systems, we can help you understand complex environments, optimise operational decision making, and undertake the data-driven design of products and solutions.

At McLaren Applied, virtual product development covers every aspect of the product lifecycle, from the very beginning of the development process all the way through to when the product is in service.


We help you to understand what your ideal product looks like by giving you an insight into high-level concepts, the architecture choices that surround them and, crucially, assist you in making informed decisions that will ultimately influence overall performance.


We enable you to develop solutions with increased performance – faster and more efficiently – by taking an outcome-led and data-driven design approach. This means you can realise the design of a product or system that is as close to perfection as possible. 


Condition Insight provides you with an understanding of the performance of your process, system, device or asset – in the past, present and future. Using a combination of physics and machine learning approaches, we perform robust multi-variate anomaly detection and can predict critical events.


Real-time and strategic decision support systems provide insight into when and how to react to unforeseen events that cause you to deviate from your optimal plan. Not only can Decision Insight provide the likely outcomes given a selected decision, it can also suggest robust optimal courses of action, given competing objectives and accounting for the uncertainties in your system or process.

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