British marque McLaren Automotive is embedding end-to-end agentic AI tech across its engineering lifecycle. It is using a bespoke platform developed by Rescale, powered by Nvidia, which, according to the auto maker, applies a “perfect-fit” AI stack to enable faster design and development at scale.
McLaren can now explore more of the design space, run complex tests and simulations faster, and tune every component with greater precision. The platform also reduces manual, repetitive tasks through leveraging engineering agents.
Nick Collins, CEO of McLaren Automotive, explained, “This is a genuine strategic transformation for the business. By continuously compounding and optimizing our data, our intelligence and our engineering philosophies at unimaginable speed, we can deliver product developments at pace, while protecting the DNA of our company.”
The Rescale system is trained exclusively on McLaren data and uses Nvidia AI infrastructure, AI physics models and agentic engineering libraries. It connects McLaren’s CAE, systems engineering and design into a unified AI data fabric that continuously learns and optimizes, while adhering to McLaren’s quality standards and performance characteristics.
“Our foundational platform allows McLaren to leverage the latest agentic engineering technologies powered by Nvidia AI infrastructure, providing a compounding source of competitive advantage for engineers in critical areas of product development, such as carbon materials, structural dynamics, durability and ultimately the programmatic scaling of engineering excellence across every discipline, to deliver world-class products faster,” said Joris Poort, founder and CEO of Rescale.
Tim Costa, VP and GM, computational engineering at Nvidia, said, “The future of automotive engineering is being rewritten by agentic AI and advanced simulation, turning decades of design heritage into a live, generative engine that accelerates every stage of the vehicle lifecycle. By integrating Rescale’s unified control layer with Nvidia’s open models for agentic AI and accelerated physics, McLaren is compressing years of traditional simulation into hours of real-time design exploration.”
As McLaren explained, AI-accelerated workflows enable the company to operate and explore beyond the constraints of traditional physics and computational modeling methods. AI-driven physics greatly reduces simulation time, with every test feeding new data back into the system to continuously improve surrogate models and AI agents’ understanding of the physical world.
Engineers can evaluate thousands of design iterations in hours, spanning multiple physics and engineering domains. This fundamentally changes how quickly an optimal design can be achieved. Machine learning models also enable instant predictions of manufacturing performance, for example in the production of high-performance carbon-fiber structures and components.
Rescale helps McLaren automate complex, repetitive engineering tasks, boosting expert productivity by up to three times on Nvidia-powered infrastructure. Its platform builds engineering knowledge graphs that capture insights from previous work, powering agentic engineering workflows and accelerating product development decisions.
