McLaren Automotive has deployed an end-to-end agentic artificial intelligence (AI) platform across its engineering lifecycle, in partnership with Rescale and Nvidia.
Rescale’s digital engineering platform, powered by an Nvidia infrastructure, creates a unified environment that connects McLaren’s computer-aided engineering (CAE), systems engineering and design into a single AI ‘data fabric’. The platform is trained exclusively on McLaren data and continuously learns and optimises, while adhering to the company’s quality standards and performance characteristics.
Nick Collins, CEO of McLaren Automotive, said of the move, “By continuously compounding and optimising 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.”
AI-driven physics simulation reduces test cycle times, with each test feeding new data back into the system to improve surrogate models and agents’ understanding of physical behaviour. McLaren says that engineers can use the systems to evaluate thousands of design iterations within hours across multiple physics and engineering domains, enabling more rapid optimisation compared with traditional computational modelling.
Machine learning models enable instant performance prediction for manufacturing processes, including the production of high-performance carbon fibre structures and components. According to Rescale, the platform’s agentic engineering capabilities automate complex repetitive tasks, which can increase the productivity of McLaren’s experts three-fold.
Rescale’s platform also builds engineering knowledge graphs that capture insights from previous work, which in turn power agentic workflows and accelerate product development decisions.
Joris Poort, founder and CEO of Rescale, said, “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.”
Tim Costa, vice president and general manager of computational engineering at Nvidia, added, “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.”
