Industrial Software Leaders Build Secure, Autonomous AI Engineers With NVIDIA NemoClaw

<div id="bsf_rt_marker"></div><p><span style="font-weight: 400;">Accelerated computing has revolutionized industrial engineering, compressing simulation times from weeks to hours. </span></p> <p><span style="font-weight: 400;">Today’s remaining challenges sit in the end-to-end workflow surrounding the simulations: computer-aided design, meshing, simulation setup and debugging, as well as post-processing and generating summary reports of these processes. </span></p> <p><span style="font-weight: 400;">At GTC Taipei at COMPUTEX, NVIDIA and more than a dozen engineering software providers <a target="_blank" href="https://nvidianews.nvidia.com/news/enterprise-software-leaders-build-ai-agents-with-nvidia">are showcasing</a> how autonomous AI agents automate this entire workflow.</span></p> <p><span style="font-weight: 400;">These AI engineers are based on </span><a target="_blank" href="https://www.nvidia.com/en-us/ai/nemoclaw/"><span style="font-weight: 400;">NVIDIA NemoClaw</span></a><span style="font-weight: 400;">, an open blueprint for building specialized, long-running agents with a secure runtime and frontier models. </span></p> <p><span style="font-weight: 400;">NemoClaw includes a choice of harness — meaning it can be integrated with various orchestration frameworks enterprises use to deploy and coordinate agents, such as OpenClaw and Hermes — as well as a model router and </span><a target="_blank" href="https://www.nvidia.com/en-us/ai-data-science/products/nemo/"><span style="font-weight: 400;">NVIDIA NeMo</span></a><span style="font-weight: 400;"> libraries for customization. </span></p> <p><span style="font-weight: 400;">Users can easily deploy NemoClaw from </span><a target="_blank" href="https://www.nvidia.com/en-us/products/workstations/dgx-spark/"><span style="font-weight: 400;">NVIDIA DGX Spark</span></a><span style="font-weight: 400;"> personal AI supercomputers, as well as through enterprise data centers and cloud service providers. </span><a target="_blank" href="https://build.nvidia.com/openshell"><span style="font-weight: 400;">NVIDIA OpenShell</span></a><span style="font-weight: 400;"> — the open source runtime at its core — governs how each agent accesses files, networks and tools, enforcing policy-based security at every layer.</span></p> <h2><b>Industrial Engineering Leaders Build AI Agents Across Design, Engineering, Simulation</b></h2> <p><span style="font-weight: 400;">Industrial software leaders are building AI engineers for computer-aided engineering (CAE) and electronic design automation (EDA) use cases across automotive, aerospace, semiconductors and manufacturing.</span></p> <p><a target="_blank" href="https://www.cadence.com/en_US/home/company/newsroom/press-releases/pr/2026/cadence-unveils-industryas-first-fully-autonomous-virtual.html"><span style="font-weight: 400;">Cadence</span></a><span style="font-weight: 400;"> is building an autonomous register-transfer level (RTL) engineer with NemoClaw that orchestrates </span><span style="font-weight: 400;">Cadence</span><span style="font-weight: 400;"> Design Systems ChipStack for design and verification. The workflow was featured yesterday in a GTC Taipei keynote demo and is cutting time for RTL verification — a key step in digital circuit design — from weeks to hours.</span></p> <p><iframe title="Cadence Cuts Chip Verification From Weeks to Hours With AI Engineers and NVIDIA OpenShell" width="1200" height="675" src="https://www.youtube.com/embed/k0Rgc3ZH5Co?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe></p> <p><a target="_blank" href="https://blog.3ds.com/topics/company-news/ai-factory-virtual-twins"><span style="font-weight: 400;">Dassault Systèmes</span></a><span style="font-weight: 400;"> is actively productizing the 3DEXPERIENCE Agentic Platform to operate long-running and autonomous agents for design, simulation and manufacturing operations, in a secured environment powered by NVIDIA NemoClaw and OpenShell.  </span></p> <p><a target="_blank" href="https://news.siemens.com/en-us/siemens-fuse-eda-ai-agent/"><span style="font-weight: 400;">Siemens</span></a><span style="font-weight: 400;"> is integrating NVIDIA NemoClaw and OpenShell into Fuse EDA AI Agent, a purpose-built autonomous agent that plans and orchestrates domain-scoped multi-tool workflows across semiconductor, 3D integrated circuit and printed circuit board system design.</span></p> <p><a target="_blank" href="https://news.synopsys.com/2026-03-16-Synopsys-Showcases-NVIDIA-Partnership-Impact-and-Ecosystem-Innovation-at-GTC-2026"><span style="font-weight: 400;">Synopsys</span></a><span style="font-weight: 400;"> is collaborating with NVIDIA to apply agents to end-to-end engineering workflows with NVIDIA NemoClaw. Ansys Icepak, part of the Synopsys portfolio, is being demoed on the COMPUTEX show floor this week, used within a NemoClaw-based autonomous AI engineer to mesh, simulate and optimize GPU electronics cooling designs.</span></p> <p><img fetchpriority="high" decoding="async" class="aligncenter wp-image-93797 size-large" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-1680x1009.jpg" alt="" width="1680" height="1009" srcset="https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-1680x1009.jpg 1680w, https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-960x577.jpg 960w, https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-1280x769.jpg 1280w, https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-1536x923.jpg 1536w, https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-scaled.jpg 2048w, https://blogs.nvidia.com/wp-content/uploads/2026/06/synopsys-image-630x378.jpg 630w" sizes="(max-width: 1680px) 100vw, 1680px" /></p> <p style="text-align: center;"><em>Image courtesy of Synopsys.</em></p> <h2><b>Startups Extend the Reach of Agentic AI</b></h2> <p><span style="font-weight: 400;">In addition, cutting-edge startups are building AI engineers for their workflows — all using NVIDIA NemoClaw.</span></p> <p><span style="font-weight: 400;">Flexcompute</span><span style="font-weight: 400;"> is applying OpenShell to its Tidy3D and PhotonForge agents for multiphysics co-packaged optics design. Flexcompute’s autonomous AI workflow combines optical, electrical and thermal simulation to explore thousands of design variants overnight, producing higher-performing components with lower energy consumption. NVIDIA is using Flexcompute technology for the design and optimization of advanced optical and photonic devices.</span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-1" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/flexcompute-video-cut-1.mp4?_=1" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/flexcompute-video-cut-1.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/flexcompute-video-cut-1.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><em>Video courtesy of Flexcompute.</em></p> <p><span style="font-weight: 400;">Luminary</span><span style="font-weight: 400;"> is building a long-running AI engineer using NemoClaw to dramatically reduce the time and complexity of training AI physics models by autonomously orchestrating data generation, machine learning model selection, and training and re-training loops.</span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-2" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/luminary-video-cut.mp4?_=2" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/luminary-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/luminary-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of Luminary.</span></i></p> <p><span style="font-weight: 400;">Neural Concept</span><span style="font-weight: 400;"> is deploying an agent for electric motor design. The workflow chains electromagnetic, structural and noise, vibration and harness simulations in a multistep engineering pipeline. </span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-3" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/neural-concept-video-cut.mp4?_=3" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/neural-concept-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/neural-concept-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of Neural Concept.</span></i></p> <p><a target="_blank" href="https://www.ntop.com/resources/blog/ntop-and-jetzero-are-building-the-next-generation-of-aircraft-design-with-nvidia-nemoclaw/"><span style="font-weight: 400;">nTop</span></a><span style="font-weight: 400;">, the geometry engine behind JetZero&#8217;s blended-wing-body aircraft program, is using NVIDIA NemoClaw to run autonomous design workflows that compress days of geometry iteration into hours.</span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-4" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/ntop-video-cut.mp4?_=4" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/ntop-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/ntop-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of nTop.</span></i></p> <p><span style="font-weight: 400;">PhysicsX</span><span style="font-weight: 400;"> is partnering with the </span><span style="font-weight: 400;">Microsoft</span><span style="font-weight: 400;"> Surface team to build an electronics thermal simulation agent that compresses weeks of manual CAE workflows into automated, AI-driven design cycles. Bringing together the PhysicsX platform, Microsoft Discovery and NVIDIA NemoClaw, the agent automates the full thermal simulation lifecycle for consumer devices such as Microsoft Surface laptops — from mesh sensitivity analysis and simulation data generation, through physics AI model training and optimization-loop execution, to continuous accuracy monitoring across the design exploration process.</span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-5" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/physicx-video-cut.mp4?_=5" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/physicx-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/physicx-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of PhysicsX.</span></i></p> <p><a target="_blank" href="https://p-1.ai/computex2026"><span style="font-weight: 400;">P-1 AI</span></a> <span style="font-weight: 400;">is building Archie, an AI mechanical and electrical engineer that already works with data center cooling and critical power systems, and will soon work for automotive, aerospace and national security use cases. In a workflow representative of its work with Daikin Applied Americas, Archie synthesizes requirements, selects components, runs design trade studies and produces engineering artifacts to help industrial manufacturers scale engineering capacity.</span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-6" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/p-1-ai-video-cut.mp4?_=6" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/p-1-ai-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/p-1-ai-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of P-1 AI.</span></i></p> <p><span style="font-weight: 400;">SimScale</span><span style="font-weight: 400;"> is adopting NVIDIA NemoClaw to build autonomous simulation agents for hundreds of cross-industry engineering use cases, including noise, vibration and harshness analysis, automating workflows that previously required multiple engineers working over several weeks. </span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-7" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/simscale-video-cut.mp4?_=7" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/simscale-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/simscale-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of SimScale.</span></i></p> <p><a target="_blank" href="https://www.synera.io/press/synera-nvidia-nemoclaw-ai-agents-design-simulation"><span style="font-weight: 400;">Synera</span></a><span style="font-weight: 400;"> is building an engineering agent for injection molding — a manufacturing process used to efficiently mass-produce identical parts by injecting molten material, usually plastic, into a custom mold — with </span><span style="font-weight: 400;">Autodesk</span><span style="font-weight: 400;"> Moldflow, NVIDIA OpenShell with OpenClaw, as well as Nemotron models. </span></p> <div style="width: 1200px;" class="wp-video"><video class="wp-video-shortcode" id="video-93790-8" width="1200" height="675" preload="metadata" controls="controls"><source type="video/mp4" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/synera-video-cut.mp4?_=8" /><a href="https://blogs.nvidia.com/wp-content/uploads/2026/06/synera-video-cut.mp4">https://blogs.nvidia.com/wp-content/uploads/2026/06/synera-video-cut.mp4</a></video></div> <p>&nbsp;</p> <p style="text-align: center;"><i><span style="font-weight: 400;">Video courtesy of Synera.</span></i></p> <p><i><span style="font-weight: 400;">Learn more about </span></i><a target="_blank" href="https://www.nvidia.com/en-us/solutions/cae/"><i><span style="font-weight: 400;">NVIDIA technologies for CAE</span></i></a><i><span style="font-weight: 400;"> and watch NVIDIA founder and CEO Jensen Huang’s </span></i><a target="_blank" href="https://www.youtube.com/live/wSp6AiNIrsY?si=rHGp_wZpqNmlOpmx"><i><span style="font-weight: 400;">GTC Taipei keynote in replay</span></i></a><i><span style="font-weight: 400;">.</span></i></p>