NVIDIA NemoClaw targets autonomous engineering workflows

NVIDIA is positioning NemoClaw as a secure blueprint for long-running autonomous engineering agents across design, simulation and manufacturing. Major software vendors and startups are using it to automate workflows that have traditionally required extensive manual coordination.

Accelerated computing has revolutionized industrial engineering, compressing simulation times from weeks to hours. 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. At GTC Taipei at COMPUTEX, NVIDIA and more than a dozen engineering software providers are showcasing how autonomous Artificial Intelligence agents automate this entire workflow.

These Artificial Intelligence engineers are based on NVIDIA NemoClaw, an open blueprint for building specialized, long-running agents with a secure runtime and frontier models. NemoClaw includes a choice of harness, allowing integration with orchestration frameworks such as OpenClaw and Hermes, along with a model router and NVIDIA NeMo libraries for customization. Users can deploy NemoClaw from NVIDIA DGX Spark personal Artificial Intelligence supercomputers, enterprise data centers and cloud service providers, while NVIDIA OpenShell governs how each agent accesses files, networks and tools through policy-based security.

Large industrial software providers are applying the platform across computer-aided engineering and electronic design automation in automotive, aerospace, semiconductors and manufacturing. Cadence is building an autonomous register-transfer level engineer with NemoClaw and says the workflow is cutting time for RTL verification from weeks to hours. Dassault Systèmes is productizing the 3DEXPERIENCE Agentic Platform for long-running autonomous agents in design, simulation and manufacturing operations, while Siemens is integrating NemoClaw and OpenShell into its Fuse EDA AI Agent for semiconductor, 3D integrated circuit and printed circuit board system design. Synopsys is collaborating with NVIDIA on end-to-end engineering workflows, including a COMPUTEX demo using Ansys Icepak within a NemoClaw-based autonomous Artificial Intelligence engineer for GPU electronics cooling design.

Startups are extending the same approach into more specialized workflows. Flexcompute is applying OpenShell to Tidy3D and PhotonForge agents for multiphysics co-packaged optics design, with a workflow that can explore thousands of design variants overnight. Luminary is building a long-running Artificial Intelligence engineer to automate data generation, model selection, and training and re-training loops for physics models. Neural Concept is deploying an agent for electric motor design, and nTop is using NVIDIA NemoClaw to run autonomous design workflows that compress days of geometry iteration into hours.

Other deployments focus on manufacturing and product engineering. PhysicsX is partnering with the Microsoft Surface team on an electronics thermal simulation agent that compresses weeks of manual CAE workflows into automated, Artificial Intelligence-driven design cycles. P-1 AI is building Archie, an Artificial Intelligence mechanical and electrical engineer for data center cooling, critical power systems and additional industrial sectors. SimScale is adopting NVIDIA NemoClaw for autonomous simulation agents across hundreds of engineering use cases, and Synera is building an engineering agent for injection molding with Autodesk Moldflow, NVIDIA OpenShell with OpenClaw, and Nemotron models.

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