Jensen Huang called OpenClaw “the operating system for personal AI” and compared it to HTML and Linux. NemoClaw is how NVIDIA makes it run securely — on anything from an RTX laptop to a DGX AI supercomputer.
NemoClaw landed on March 16 at NVIDIA’s annual GTC conference in San Jose, California — the event Huang’s team has taken to calling the “Super Bowl of AI.” The announcement positions NVIDIA not just as the company that sells the chips powering AI, but as the company that defines how autonomous AI agents run securely at every layer of the stack, from cloud infrastructure to the laptop on your desk.
The timing is deliberate. OpenClaw has become the fastest-growing open-source project in the history of software. It crossed 250,000 GitHub stars in weeks and sparked installation queues outside tech company headquarters across China and the United States. The challenge it faces is not adoption — it is trust. Security researchers have found tens of thousands of exposed OpenClaw instances on the public internet, identified critical vulnerabilities, and flagged risks around data exfiltration. NemoClaw is NVIDIA’s answer to that problem.
What NemoClaw Actually Does
The core value proposition is precision and simplicity. NemoClaw installs in a single command and immediately adds the infrastructure layer that OpenClaw was missing: privacy controls, security guardrails, and dedicated local compute for always-on agents.
The stack works as follows. NemoClaw uses NVIDIA’s Agent Toolkit software to optimize OpenClaw, then installs NVIDIA OpenShell — a newly announced runtime that runs open models in an isolated sandbox. OpenShell is what enforces policy-based security, network permissions, and data privacy controls around agents. It draws a hard boundary around what an agent can access and what it cannot, resolving one of the most serious criticisms of the current OpenClaw ecosystem.
For model access, NemoClaw is flexible. When running locally, it taps into NVIDIA Nemotron open models on the user’s dedicated system. When a task requires a frontier model, a built-in privacy router sends the request to cloud-based models without exposing sensitive local data. That combination — local open models for privacy-sensitive tasks, frontier cloud models for capability-intensive ones — gives agents genuine depth without compromising user control.
The always-on design is central to how NVIDIA frames the product. Agents need to run continuously to be useful: building tools, completing background tasks, monitoring workflows, learning new skills. NemoClaw is explicitly designed to run around the clock on dedicated hardware — NVIDIA GeForce RTX PCs and laptops, NVIDIA RTX PRO workstations, and for enterprise deployments, NVIDIA DGX Station and DGX Spark AI supercomputers.
Peter Steinberger, OpenClaw’s creator — who has since joined OpenAI — said: “OpenClaw brings people closer to AI and helps create a world where everyone has their own agents. With NVIDIA and the broader ecosystem, we’re building the claws and guardrails that let anyone create powerful, secure AI assistants.”
What Jensen Huang Said at GTC 2026
Huang used the GTC stage to frame the stakes in terms that did not leave much room for understatement.
“OpenClaw is the number one. It is the most popular open-source project in the history of humanity, and it did so in just a few weeks,” he said. He drew a direct parallel to the personal computer era: “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.”
On the broader case for AI agents: “Every company in the world today needs to have an OpenClaw strategy, an agentic system strategy. This is the new computer. This is as big of a deal as HTML, as big of a deal as Linux.”
Huang also gave investors the revenue number they came for. He said he expects “at last” $1 trillion in NVIDIA revenue through 2027 — a projection grounded, in his telling, in a structural shift in what AI is being used for. “AI is able to do productive work,” Huang said, “and therefore the inflection point of inference has arrived.”
NVIDIA is, as Wedbush analyst Dan Ives noted ahead of GTC, now “focused beyond just computing with a major focus on the future of networking in this new world of AI.”
The Hardware Shift Behind NemoClaw
NemoClaw did not arrive alone. Huang used GTC to announce that Vera Rubin, NVIDIA’s next-generation computing platform, now has all seven of its chips in full production. The platform includes a new CPU-based computing rack — a meaningful departure for a company built on GPUs. CPUs are better suited to the types of reasoning and orchestration processes that agents require during inference and task execution, which is why NVIDIA is building them into its own systems rather than relying entirely on external suppliers.
NVIDIA also confirmed the integration of Groq’s language processing units (LPUs) into its systems — a consequence of the $20 billion deal the two companies struck in November 2025. Groq’s LPUs process language-type tasks at high speed with low energy cost, and their inclusion signals that NVIDIA sees agent inference as a distinct compute workload, one that GPUs alone are not optimally designed to handle.
The company also announced a space module for Vera Rubin — an early signal that NVIDIA is positioning its AI infrastructure for data centers in orbit as terrestrial real estate becomes a constraint.
NemoClaw and the Agent Security Problem
OpenClaw’s security vulnerabilities are not hypothetical. At the same time Huang was speaking in San Jose, security researchers had already documented over 40,000 exposed OpenClaw instances on the public internet, a critical remote hijacking flaw called “ClawJacked,” and confirmed data exfiltration from third-party skills. China’s central government had just restricted state-owned enterprises from using OpenClaw on official systems.
NemoClaw’s direct response to all of this is OpenShell’s isolated sandbox and policy-based access controls. Agents running inside NemoClaw can access the systems and files they need — calendars, email, local documents, external APIs — while enforcing defined permission and privacy settings that users set in advance. The architecture is designed so that the agent cannot silently expand its access or communicate externally beyond what the user has authorized.
Whether NemoClaw resolves the security concerns comprehensively enough for enterprise adoption remains to be tested in real-world deployments. What it does accomplish is giving OpenClaw a credible, NVIDIA-backed security posture for the first time. For enterprises that want to deploy autonomous agents at scale — and the OpenClaw wave has created enormous enterprise demand — NemoClaw is the first tool that addresses the fundamental infrastructure gap between capability and control.
For ongoing analysis of NVIDIA’s AI strategy, OpenClaw developments, and the enterprise agent market, The Tech Marketer covers how these platforms are reshaping business technology decisions.
FAQ
Q1: What is NemoClaw and what problem does it solve for OpenClaw? NemoClaw is an NVIDIA software stack for the OpenClaw agent platform, announced at GTC 2026 on March 16 in San Jose. It installs in a single command and adds the security and privacy infrastructure that OpenClaw previously lacked — including an isolated sandbox via NVIDIA OpenShell, policy-based access controls, a privacy router for cloud model access, and dedicated local compute on NVIDIA hardware. It addresses the core concerns raised by security researchers about exposed OpenClaw instances, data exfiltration risks, and the ClawJacked vulnerability.
Q2: What is NVIDIA OpenShell and how does it work inside NemoClaw? NVIDIA OpenShell is a newly announced runtime that ships as part of NemoClaw. It creates an isolated sandbox around OpenClaw agents, enforcing data privacy, network access controls, and security guardrails. It allows agents to run NVIDIA Nemotron open models locally for privacy-sensitive tasks and routes requests to frontier cloud models via a privacy router when greater capability is needed — without exposing local user data to cloud services.
Q3: What hardware does NemoClaw run on? NemoClaw is designed to run on any dedicated NVIDIA platform. For personal and professional use, it supports GeForce RTX PCs and laptops, and NVIDIA RTX PRO workstations. For enterprise deployments, it supports NVIDIA DGX Station and DGX Spark AI supercomputers. The emphasis on dedicated hardware reflects NVIDIA’s position that always-on agents need dedicated compute to run continuously and build new skills around the clock.
Q4: What did Jensen Huang say about OpenClaw and NemoClaw at GTC 2026? Huang said OpenClaw is “the operating system for personal AI” — drawing a direct parallel to Mac and Windows for the personal computer era. He called it “the most popular open-source project in the history of humanity.” On the broader significance: “Every company in the world today needs to have an OpenClaw strategy. This is the new computer. This is as big of a deal as HTML, as big of a deal as Linux.” He also projected “at last” $1 trillion in NVIDIA revenue through 2027, grounded in what he called the structural arrival of the AI inference inflection point.
Q5: How does NemoClaw relate to NVIDIA’s broader hardware and computing strategy announced at GTC 2026? NemoClaw is part of a larger set of announcements that signal NVIDIA’s strategic shift from pure GPU dominance toward full-stack AI agent infrastructure. At GTC, Huang also announced that Vera Rubin — NVIDIA’s next-generation computing platform — now has all seven chips in production, including a new CPU-based computing rack better suited to agent inference workloads. NVIDIA also confirmed integration of Groq’s LPUs into its systems following a $20 billion deal in November 2025, and announced a space module for Vera Rubin targeting orbital data centers.
Sources & References
- NVIDIA Newsroom — NVIDIA Announces NemoClaw for the OpenClaw Community
- CNN — The World’s Most Valuable Company Just Sent Another Signal That AI Agents Are Going to Be Everywhere
- WSJ — Nvidia Software Aims to Bring OpenClaw to the Enterprise
- NVIDIA Newsroom — AI Agents (OpenShell announcement)
- NVIDIA Blog — GTC 2026 News Roundup
