NVIDIA NemoClaw AI-powered demo showcasing rapid RTL verification, reducing time from weeks to hours at GTC Taipei conference

Editorial illustration for NVIDIA NemoClaw demo cuts RTL verification from weeks to hours at GTC Taipei

NVIDIA NemoClaw demo cuts RTL verification from weeks to...

NVIDIA NemoClaw demo cuts RTL verification from weeks to hours at GTC Taipei

By AI Daily Post Edited by Brian Petersen, Editor-in-Chief

June 3, 2026 • 2 min read

Industrial software firms are turning to NVIDIA’s NemoClaw to turn design and verification tasks into autonomous workflows. Cadence showcased an “autonomous register‑transfer level (RTL) engineer” that steers its Design Systems ChipStack, and the GTC Taipei keynote demonstrated that the same workflow can shrink RTL verification—from a multi‑week bottleneck to a matter of hours. While the demo focused on digital circuit design, the same AI‑driven approach is spreading across automotive, aerospace, semiconductor and manufacturing sectors.

Dassault Systèmes is packaging the 3DEXPERIENCE Agentic Platform with NemoClaw and OpenShell to run long‑running agents for design, simulation and manufacturing in a secured environment. Siemens is embedding the same stack into its Fuse EDA AI Agent, a tool that plans and coordinates multi‑tool workflows for chips, 3‑D ICs and PCBs. Synopsys, meanwhile, is partnering with NVIDIA to apply NemoClaw across end‑to‑end engineering pipelines; a demo of Ansys Icepak on the COMPUTEX floor shows the agent meshing, simulating and optimizing GPU cooling designs.

The collective effort points to a broader push for AI‑powered engineers that can manage complex, domain‑specific toolchains with minimal human oversight.

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.
Dassault Systèmes 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.
Siemens 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.
Synopsys 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.
Image courtesy of Synopsys.

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

Why this matters

We see AI agents stepping into the very heart of hardware design, where weeks‑long RTL verification now runs in hours according to the GTC Taipei demo. Industrial software firms claim their AI engineers span CAE and EDA tasks across automotive, aerospace, semiconductor and manufacturing domains, promising tighter design loops. For developers, the speedup suggests more frequent test iterations and potentially lower time‑to‑market, but the demo doesn’t reveal how the agents handle corner‑case bugs or maintain verification coverage.

Founders may view the reduction as a lever for cost savings, yet integrating such agents into existing toolchains could demand substantial effort and new expertise. Researchers are left with a clear example of autonomous AI applied to a traditionally manual verification stage, though the robustness of the approach under diverse design families remains uncertain. A bold claim.

In short, the technology hints at a shift in how we allocate engineering resources, but practical adoption will depend on proven reliability and clear integration pathways.