<p>NVIDIA, at its GTC conference, has announced the <a title="" href="http://www.nvidia.com/nemoclaw" target="_blank" rel="nofollow noopener"><u>NVIDIA NemoClaw</u></a> stack for the OpenClaw agent platform — which lets users install <a title="" href="https://nvidianews.nvidia.com/news/nvidia-expands-open-model-families-to-power-the-next-wave-of-agentic-physical-and-healthcare-ai" target="_blank" rel="nofollow noopener"><u>NVIDIA Nemotron</u></a> models and the newly announced <a title="" href="https://nvidianews.nvidia.com/news/ai-agents" target="_blank" rel="nofollow noopener"><u>NVIDIA OpenShell</u></a> runtime in a single command — adding privacy and security controls to make self-evolving, autonomous AI agents, or claws, more trustworthy, scalable and accessible to the world.</p>
<p>“OpenClaw opened the next frontier of AI to everyone and became the fastest-growing open source project in history,” said Jensen Huang, founder and CEO of NVIDIA. “Mac and Windows are the operating systems for the personal computer. OpenClaw is the operating system for personal AI. This is the moment the industry has been waiting for — the beginning of a new renaissance in software.”</p>
<p>“OpenClaw brings people closer to AI and helps create a world where everyone has their own agents,” said Peter Steinberger, creator of OpenClaw. “With NVIDIA and the broader ecosystem, we’re building the claws and guardrails that let anyone create powerful, secure AI assistants.”</p>
<p>NemoClaw uses <a title="" href="https://nvidianews.nvidia.com/news/ai-agents" target="_blank" rel="nofollow noopener"><u>NVIDIA Agent Toolkit</u></a> software to optimize OpenClaw in a single command. It installs <a title="" href="http://build.nvidia.com/openshell" target="_blank" rel="nofollow noopener"><u>OpenShell</u></a> to provide open models and an isolated sandbox that adds data privacy and security to autonomous agents. This provides the missing infrastructure layer beneath claws to give them the access they need to be productive, while enforcing policy-based security, network and privacy guardrails.</p>
<p>NemoClaw uses any coding agent. With open agents, it can tap open models — including NVIDIA Nemotron — running locally on the user’s dedicated system. Using a privacy router, agents can use frontier models running in the cloud. This combination of local and cloud models provides a foundation for agents to develop and learn new skills to complete tasks according to defined privacy and security guardrails.</p>
<p>Always-on agents need dedicated computing to build software and tools, and complete tasks. NemoClaw for OpenClaw can run on any dedicated platform — including dedicated <a title="" href="https://www.nvidia.com/en-us/ai-on-rtx/" target="_blank" rel="nofollow noopener"><u>NVIDIA GeForce RTX™ PCs and laptops</u></a> or <a title="" href="https://www.nvidia.com/en-us/products/workstations/" target="_blank" rel="nofollow noopener"><u>NVIDIA RTX™ PRO -powered workstations</u></a>, as well as <a title="" href="https://blogs.nvidia.com/blog/gtc-2026-news/#dgx-spark-station" target="_blank" rel="nofollow noopener"><u>NVIDIA DGX Station™ and NVIDIA DGX Spark</u></a>™ AI supercomputers — to provide local computing for autonomous agents to run around the clock.</p>

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