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Rescale has announced a proposed collaboration with three US Department of Energy national laboratories—Lawrence Berkeley, Oak Ridge, and Lawrence Livermore—to make DOE simulation codes accessible to American industry through agentic AI. The partnership, called the Agentic HPC Pipeline Initiative, would use Rescale's digital engineering platform to automate complex simulation workflows. The initiative aims to address the expertise gap that has historically prevented manufacturers from using sophisticated DOE-developed engineering codes. Rescale's AI agents automate tasks like mesh configuration, hardware selection and solver tuning, allowing engineers to run advanced simulations without specialist knowledge. The collaboration builds on existing work with Oak Ridge's Manufacturing Demonstration Facility. The three laboratories bring complementary expertise across fluid dynamics, materials science, additive manufacturing and energy systems.

Rescale and U.S. National labs form initiative to bring DOE simulation codes to American industry. June 9, 2026 Lawrence Berkeley, Oak Ridge, and Lawrence Livermore national laboratories propose partnering with Rescale to make DOE simulation codes accessible through agentic AI SAN FRANCISCO, CA - June 9, 2026 - Rescale, the digital engineering platform built for the AI era, today announced a landmark proposed collaboration with three premier U.S. Department of Energy national laboratories: Lawrence Berkeley National Laboratory (LBNL), Oak Ridge National Laboratory (ORNL), and Lawrence Livermore National Laboratory (LLNL). The proposed collaboration builds on existing work with the ORNL Manufacturing Demonstration Facility to bring world-class simulation codes developed at the national labs to American industry at scale. Operating as the Agentic HPC Pipeline Initiative (AHPI), the partnership would use recently launched agentic digital engineering capabilities on the Rescale platform to accelerate U.S. manufacturers' deployment of DOE-developed codes in production engineering environments. For decades, the Department of Energy has invested in developing some of the world's most sophisticated engineering simulation codes, spanning advanced manufacturing, materials science, energy systems, and beyond. Yet operating these codes has required specialized expertise to configure and maintain the software on HPC infrastructure as well as run the advanced simulations themselves, keeping their power out of reach for most of U.S. industry. The AHPI consortium is designed to close these infrastructure and expertise gaps. By hosting DOE codes on the Rescale digital engineering platform and pairing them with agentic AI that guides users through every step, engineers across U.S. industry can translate intent into fully autonomous simulation workflows. Tasks that previously demanded deep specialist knowledge, such as mesh configuration, hardware selection, solver tuning, and checkpoint management, are now handled autonomously by these simulation-native agents. "America's national laboratories have spent decades building the most powerful engineering simulation software in the world, like our AMReX framework, but the depth of domain expertise required to configure and validate these tools has kept them out of reach for many manufacturers," said Peter Nugent, Division Deputy for Science in the Applied Math & Computational Research Division at LBNL and Principal Investigator of the AHPI project. "By integrating our codes with Rescale's AI agents, we are fundamentally shifting the paradigm. We are replacing the manual burden of solver selection, checkpointing, and hardware configuration with intelligent automation. This translates scientific intent directly into computational reality." Rescale's in-platform agents are already orchestrating manufacturing codes developed at ORNL's Manufacturing Demonstration Facility, enabling engineers to integrate manufacturing data into automated workflows. "At ORNL, we are focused on pushing the boundaries of what is possible in physical production," said Ramanan Sankaran, ORNL Lead. "We are already seeing our advanced manufacturing codes from the Manufacturing Demonstration Facility being orchestrated by in-platform agents. By reducing the expertise bottleneck in job configuration and allowing engineers to train surrogate models on their simulation data using in-platform agents, we are enabling U.S. manufacturers to innovate at speeds that were previously impossible." The proposed collaboration with LLNL builds on the established HPC for Energy Innovation (HPC4EI) program, which connects U.S. companies with national laboratory expertise and resources in high performance computing, modeling and simulation. "Through HPC4EI, LLNL has a long and successful history of bridging the gap between national lab supercomputing and real-world industrial applications," said Aaron Fisher, LLNL Lead. "However, scaling that impact requires a new approach to user accessibility. We believe the use of agentic AI will lead to a step change in our ability to bring these capabilities to American industry. This effort is exploring scalable pathways to help manufacturers access AI-enabled simulation workflows beyond initial DOE engagements, while building on HPC4EI's broader mission." Together, the three laboratories bring complementary depth across fluid dynamics, phase and chemical transformations, additive manufacturing, materials science, and energy systems, covering the full breadth of advanced manufacturing applications. The Rescale platform is intended to provide secure, cloud-native access to these codes through an intuitive, agent-augmented interface that requires no specialized HPC expertise to operate. "In the United States, both industry and the national labs have made extraordinary investments in computing infrastructure and simulation software," said Joris Poort, CEO of Rescale. "Rescale's digital engineering platform serves as the bridge that brings both investments together in one place and puts them to work accelerating innovation for American industry. By pairing the world's best simulation codes with AI agents that automate the complex workflows around them, we are giving American manufacturers a compounding advantage to accelerate progress, which is the ability to explore design spaces, validate materials, and optimize manufacturing processes at speeds and scales that were previously out of reach." The AHPI initiative represents a broader strategic vision for the role of AI in closing the gap between government-funded scientific capability and commercial industrial application. As AI-powered simulation becomes increasingly critical to how products are designed and built, the companies with access to the best tools will have a meaningful edge. AHPI is committed to making sure those tools are within reach for U.S. industry. The Rescale platform, including the capabilities powering the AHPI consortium, is available now. For more information, visit rescale.com. About Rescale Rescale is the digital engineering platform built for the AI era. The Rescale platform integrates intelligent HPC, advanced modeling and simulation, agentic digital engineering, and AI physics to create compounding value that accelerates product development and empowers digital transformation. The Rescale platform delivers the world's largest network of engineering and R&D applications, intelligent automation, and computing infrastructure to enterprises across aerospace, automotive, energy, life sciences, semiconductor, manufacturing, and the public sector. Rescale is backed by leading investors such as NVIDIA, Sam Altman, Jeff Bezos, Paul Graham, Peter Thiel, Microsoft, Samsung, Hitachi, University of Michigan, and others. Rescale has a global customer base that includes Applied Materials, General Motors Motorsports, SLB, and the U.S. Department of Defense. For more information, visit rescale.com.

Rescale, a digital engineering platform, has launched agentic digital engineering capabilities alongside advances in AI physics and compute economics to accelerate product development for R&D teams. The platform introduces simulation-native AI agents that automate workflows including input validation, troubleshooting and report generation, whilst maintaining human oversight. The company has expanded its AI physics operating system into an end-to-end environment for creating production-ready surrogate models from simulation data. Organisations using these capabilities report 1,000x faster simulations and 90% reductions in full-stack simulation costs, compressing months-long studies into days. Daikin Industries is deploying Rescale across its global R&D organisation after significantly reducing manual simulation data-management efforts. The platform serves customers across aerospace, automotive, energy, life sciences and manufacturing sectors.