Rescale, a digital engineering platform that helps companies run complex simulations and calculations in the cloud, announced today that it has raised $115 million in Series D funding to accelerate the development of AI-powered engineering tools that can dramatically speed up product design and testing.
The funding round, which brings Rescale’s total capital raised to more than $260 million, included investments from Applied Ventures, Atika Capital, Foxconn, Hanwha Asset Management Deeptech Venture Fund, Hitachi Ventures, NEC Orchestrating Future Fund, Nvidia, Prosperity7, SineWave Ventures, TransLink Capital, the University of Michigan, and Y Combinator.
The San Francisco-based company has drawn support from an impressive roster of early backers including Sam Altman, Jeff Bezos, Paul Graham, and Peter Thiel. This latest round aims to propel Rescale’s vision of transforming how products are designed across industries by combining high-performance computing, intelligent data management, and a new field the company calls “AI physics.”
“Rescale was founded with the mission to empower engineers and scientists to accelerate innovation by running computations and simulations more efficiently,” Joris Poort, Rescale’s founder and CEO, said in an interview with VentureBeat. “That’s exactly what we’re focused on today.”
From Boeing’s carbon fiber challenge to a $260 million startup
The company’s origins trace back to Poort’s experience working on the Boeing 787 Dreamliner more than 20 years ago. He and his co-founder Adam McKenzie were tasked with designing the aircraft’s wing using complex physics-based simulations.
“My co-founder, Adam, and I were working at Boeing, running large-scale physics simulations for the 787 Dreamliner,” Poort told VentureBeat. “It was the first fully carbon fiber commercial airplane, which posed significant engineering challenges. Most airplanes before had always been built out of aluminum, but carbon fiber has many different layers and variables that needed to be optimized.”
The challenge they faced was a lack of sufficient computing resources to run the millions of calculations needed to optimize the innovative carbon fiber design. “We couldn’t get enough compute resources. This was 20 years ago, before cloud computing existed,” he recalled. “We had to bootstrap together and cobble together resources from different organizations just to run these large-scale simulations over the weekend.”
This experience led directly to Rescale’s founding mission: build the platform they wished they had during those Boeing years.
“Rescale was founded to build the platform we wish we had, because it took us many years to develop all these capabilities,” Poort explained. “We were really just engineers trying to design the best possible plane, but we had to become applied mathematicians and computer scientists, doing all this infrastructure work just to solve engineering problems.”
How AI models are turning days of calculations into seconds
Central to Rescale’s ambitions is the concept of “AI physics” — using artificial intelligence models trained on simulation data to dramatically accelerate computational engineering. While traditional physics simulations might take days to complete, AI models trained on those simulations can deliver approximate results in seconds.
“With AI physics, you train AI models on simulation data sets, allowing you to run these simulations over 1,000 times faster,” Poort said. “The AI model provides probabilistic answers—essentially estimates—whereas traditional physics calculations are deterministic, giving you exact results.”
He offered a concrete example from one of Rescale’s customers: “General Motors motorsports, they’re designing the external aerodynamics of a Formula One vehicle. They may run thousands of these sort of fluid dynamics, aerodynamic calculations. Normally, these may take, like, about three days on, say, 1000 compute cores. Now, with an AI model, they’re able to do this in like less than a second.”
This thousand-fold acceleration allows engineers to explore design spaces much more rapidly, testing many more iterations and possibilities than previously feasible.
“The really unique advantage of AI physics is that you can verify the answers. It’s just math,” Poort emphasized. “This is different from LLMs, where you might encounter hallucinations that are difficult to validate. Many questions don’t have definitive answers, but in physics, you have concrete, verifiable solutions.”
The funding comes amid increasing enterprise investments in technologies that speed up product development. The high-performance computing market has grown to approximately $50 billion, with simulation software reaching $20 billion and product lifecycle data management about $30 billion, according to figures shared by Rescale.
What differentiates Rescale is its “compute recommendation engine,” which optimizes workloads across different cloud architectures in real-time.
“Our unique differentiation is our technology called the compute recommendation engine. This allows us to optimize workloads in real time across different architectures available across all public clouds,” Poort said. “We support 1,150 different applications with many versions, operating systems, and hardware architectures. When combined together, this creates more than 50 million different possible configurations.”
The company’s enterprise customers, which include Arm, General Motors, Samsung, SLB (formerly Schlumberger), and the U.S. Department of Defense, collectively spend over $1 billion annually to power their virtual product development and scientific discovery environments.
Beyond simulation: Data management and AI integration for modern engineering
Rescale is accelerating its roadmap in three key areas. First, expanding its library of over 1,250 applications and network of more than 500 cloud datacenters. Second, establishing unified data management and digital thread capabilities for all computing workflows. Third, enabling faster engineering through AI.
“We also have a product called Rescale Data, which focuses on creating an intelligent data layer,” Poort explained. “This is sometimes called the digital thread. Throughout the product lifecycle—whether you’re developing an aircraft, a car, or in life sciences, a medical device or drug—you need to track all that data. If an issue arises, you can look back to see when that data was created, what the input files were, and related information.”
Applied Materials, one of the investors in this round, has been working with Rescale to enhance its simulation capabilities. Rather than simply accelerating existing processes, the partnership suggests a more profound shift in how engineering knowledge is captured and applied.
The most intriguing aspect of Rescale’s approach is how it handles the transition between traditional physics simulations and AI approximations. Unlike language models where verifying accuracy can be subjective, engineering simulations have clear mathematical answers that can be checked. This verification creates a safer pathway for introducing AI into fields where precision and reliability are paramount.
While Poort acknowledges that the concept of a “foundational physics model” — an AI system trained on vast amounts of physics simulation data that could potentially discover new physics — remains aspirational, the company is focused on delivering practical value today through narrow, domain-specific AI models.
“For quantum computing, it’s still in the commercialization phase,” Poort said, distinguishing his approach from that technology. “At Rescale, our AI physics approach is fundamentally customer-centric. We’re focused on addressing concrete problems that recent advances in AI can solve today, delivering immediate, measurable ROI to our customers.”
What Silicon Valley luminaries see in engineering simulation
Rescale has benefited from the guidance of its high-profile early investors. Paul Graham, who wrote the first check into the company, continues to provide advice on company culture. Sam Altman offers insights into AI and infrastructure. Jeff Bezos brings perspective from his Blue Origin space venture, while Peter Thiel provides counsel on scaling enterprise businesses and working with government customers.
“Paul Graham was the first investor in the company—the first person who really believed in what we were doing. If you follow his essays, you know he’s been a great mentor, and I still talk to him regularly,” Poort told VentureBeat. “Sam Altman has been a supporter since the early days. He’s an incredibly smart mind in AI, and a valuable resource for understanding the latest developments in infrastructure, AI, and even energy—where all this technology is heading.”
Poort also elaborated on Bezos’s involvement: “Jeff Bezos brings an interesting perspective because of his space company, Blue Origin,” Poort explained. “We initially worked with space companies as our customers, addressing how aerospace companies could leverage cloud computing technologies.”
He added: “Jensen has a unique ability to understand both the technical elements and the future direction of technology. Having partners with long-term vision is super critical. All these individuals are very long-term thinkers, and I’m incredibly grateful to have such enduring partners in the business.”
Engineering’s cloud transition offers new possibilities
As geopolitical tensions affect industries like semiconductors and defense, Rescale is positioning itself to help customers navigate emerging regulations and shifting supply chains. The company has developed capabilities to work with sovereign clouds — country-specific cloud environments that maintain data within national borders.
“There is an emergence of sovereign clouds,” Poort noted. “Many countries are developing their own cloud infrastructure for specific use cases. Our strategy is to partner with these providers to deliver services according to customer preferences. If a Japanese customer wants to run on a Japanese cloud, for example, we can accommodate that.”
With less than 20% of the high-performance computing market currently in the cloud, Rescale sees significant growth potential as more engineering workflows migrate to cloud environments. The company’s AI physics approach could transform how products are designed across industries, potentially reducing development time and costs while improving performance.
“The key insight is that with sufficient compute capability, we can achieve much better designs,” Poort said, reflecting on his Boeing experience. What started as a frustrating challenge with limited computing resources has evolved into a vision for how engineers might work in the future. The $115 million investment signals confidence that the gap between design imagination and technical reality is narrowing – not through quantum leaps in physics, but through smarter use of existing data and simulations.
And that 787 Dreamliner wing that started it all? “If you’ve ever flown on a 787 Dreamliner,” Poort said, “you’ll notice its distinctive curved wing design. That’s the wing we helped develop, resulting in an aircraft that’s 20% more fuel efficient.”
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