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McLaren Automotive is transforming its future product development by embedding true end-to-end agentic AI across the entire engineering lifecycle.

Tailored for McLaren, Rescale’s digital engineering platform, powered by NVIDIA, applies a ‘perfect-fit’ AI stack to bring rapid speed and scale throughout the design and engineering development process.

McLaren can now explore more design space, run complex test and simulations significantly faster, tune every component with greater precision and reduce manual, repetitive tasks through leveraging engineering agents. As well as dramatically accelerating product development, it also protects McLaren’s engineering heritage by creating an environment for teams to focus on high value design and engineering thinking.

Within the Rescale environment, the platform is trained exclusively on McLaren data and utilises NVIDIA AI infrastructure, AI physics models and agentic engineering libraries. This creates a unified platform approach that connects McLaren CAE, systems engineering and design into a unified AI data fabric which continuously learns and optimises while adhering to the integrity of McLaren’s quality standards and performance characteristics.

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Motor
Transcript
00:03We have an incredibly talented team crafting our cars and our ambition is to
00:07make them as efficient as possible leveraging best tools. Investment in
00:11technology is a core priority for us and this collaboration with Rescale and
00:15NVIDIA directly supports that ambition.
00:19Traditional engineering workflows are fragmented. There are a lot of handovers,
00:24there's a lot of inconsistency of data or change of formats. Building AI
00:29tools on the Rescale digital engineering platform based on the NVIDIA AI
00:35infrastructure allows us to accelerate our engineering and product development
00:38processes. The end goal here is to have this integrated data platform where we
00:43have the design data, the simulation data and the test data all on one platform
00:46which will allow us to close the loop where the testing informs the simulation
00:50and simulation informs the design.
00:54We're using Physics AI to accelerate simulation that previously took hours or
00:59days to run and cut that time down to minutes.
01:03We're using AI agents to orchestrate the pre-processing and post-processing of that
01:08simulation. We have built agents that check process quality to make sure that only good
01:12information is passed downstream and we're building agents that believe engineers of repetitive work
01:17so that they can focus on innovation and product creation. The manufacturing process for carbon
01:24composite is very complicated. We're using AI physics to accelerate that process and through the agentic
01:31orchestration of that simulation we'll be even able to go one step further giving that simulation
01:38capability into the hands of the manufacturing practitioners so that they can parametrically optimize
01:44their manufacturing process and see the outcome in real time. It's very exciting for our teams. They are
01:51participating in a revolution in the way they work. Our past work becomes searchable, reusable and
01:58instantly available to our engineers and by leveraging AI physics and cloud technologies we are trying our
02:04best to eliminate all unnecessary manual work so we can deliver step change gains in productivity.
02:10Essentially we want to enable our people to focus on the work that truly defines McLaren. My vision is that
02:15we'll be building products leveraging code and algorithms as a base of that. We want to build better
02:22product, we want to build more product with the same resources and I'm sure leveraging our partnership
02:27with Ristail and NVIDIA will get there. For 60 years now McLaren has been pushing the boundaries of
02:34engineering. Using modern tools like AI physics or agentic engineering allows us to push those boundaries even
02:40further exploring more of the design space and making sure we're creating accelerating products for our customers.
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