NemoClaw is NVIDIA's open-source enterprise security layer for OpenClaw. It wraps AI agents in a sandboxed runtime, enforces declarative policies, and enables fully local inference — making OpenClaw safe for companies and government.
NemoClaw is an open-source enterprise security framework built by NVIDIA that wraps OpenClaw in a production-grade security and governance layer. Announced at NVIDIA GTC in March 2026, NemoClaw addresses the significant security gaps in bare OpenClaw deployments and makes AI agents viable for regulated industries, government, and enterprise at scale.
At its core, NemoClaw installs the NVIDIA OpenShell runtime — a sandboxed execution environment that isolates each agent's access to the filesystem, network, and hardware. On top of that, it adds a declarative policy engine, a privacy router for hybrid inference, and native support for NVIDIA Nemotron local language models.
The entire stack installs with a single command and is designed to be operated by teams without deep security expertise — policies are written in YAML, not code.
Everything OpenClaw lacks for production — delivered as a single, opinionated stack.
Every agent runs in NVIDIA's OpenShell — an isolated container-like environment. Agents cannot access files, network endpoints, or hardware outside their defined scope.
Define what agents can and cannot do in YAML. Block network egress to specific domains, restrict file paths, limit which Skills can be loaded — enforced at runtime, not by convention.
NemoClaw's architecture eliminates the attack surface that enabled CVE-2026-25253 and six subsequent vulnerabilities. Agents cannot be exploited into running attacker code even if the agent is compromised.
Run NVIDIA's Nemotron family of models entirely on-device. No prompts, data, or completions leave your infrastructure — critical for regulated and classified workloads.
Automatically routes prompts based on sensitivity. Public data can call cloud LLMs for best performance; sensitive data stays on local Nemotron. Configurable routing rules.
Every agent action — tool call, file read, network request — is logged with a tamper-evident audit trail. Meet compliance requirements for financial services, healthcare, and public sector.
NemoClaw wraps OpenClaw — it doesn't replace it.
OpenShell is NVIDIA's sandboxing runtime, similar in concept to a container but purpose-built for AI agent workloads. It intercepts every system call an agent makes — file open, network connect, process spawn — and evaluates it against the active policy before allowing it to proceed. This happens transparently to the agent.
NemoClaw policies are YAML files that describe what agents are allowed to do. You define allowed network egress destinations, writable file paths, permitted Skills, and inference routing rules. Policies are versioned, reviewed, and deployed like code — making them auditable.
The privacy router sits between your agents and inference providers. When an agent makes an LLM call, the router evaluates the prompt against your data classification rules and sends it to the appropriate endpoint — local Nemotron for sensitive content, a cloud provider for everything else.
Bare OpenClaw is fine for individual developers. NemoClaw is for everyone else.
Data sovereignty, air-gap requirements, and strict audit mandates make NemoClaw's local inference and policy engine essential. Agents can operate fully offline.
Patient data cannot touch cloud LLMs. NemoClaw routes sensitive prompts to on-premise Nemotron while allowing non-sensitive tasks to use cloud models for performance.
Regulatory frameworks require audit trails for automated decisions. NemoClaw's tamper-evident logs and policy enforcement satisfy financial compliance requirements.
Agents interacting with OT systems need strict network segmentation. NemoClaw's policy engine prevents agents from reaching outside their designated network zones.
Prevent proprietary research, formulae, or source code from leaking to cloud LLM providers. Local Nemotron keeps everything inside your perimeter.
When multiple teams share an agent infrastructure, NemoClaw's identity and access controls ensure each agent can only see and do what its operator is permitted to authorise.
They work together. NemoClaw is not a replacement — it's a wrapper.
| Capability | OpenClaw only | With NemoClaw |
|---|---|---|
| Agent execution | ✓ | ✓ |
| Skills marketplace | ✓ | ✓ |
| Sandbox isolation | None | OpenShell |
| Network policy enforcement | Manual / none | Declarative YAML |
| CVE-2026-25253 protection | Requires patching | Built-in |
| Local LLM inference | Via Ollama (manual) | Nemotron OOTB |
| Privacy router | Not included | Included |
| Audit trail | Not included | Tamper-evident log |
| Identity & access control | Limited | Full RBAC |
| Air-gap / offline use | Difficult | Supported |
| Regulated industry readiness | Not ready | Preview (GA: H2 2026) |
NemoClaw is NVIDIA's open-source enterprise security wrapper for OpenClaw, announced at GTC 2026. It adds sandboxed execution via OpenShell, a declarative policy engine, local Nemotron inference, a privacy router, and tamper-evident audit logging to the OpenClaw agent runtime.
Yes. NemoClaw is open-source and free. NVIDIA RTX or DGX hardware is recommended for local Nemotron inference but is optional — you can use cloud LLM providers instead.
Any time your agents touch sensitive data, serve multiple users, or operate in a regulated environment. NemoClaw provides the security isolation, policy control, and audit trail that bare OpenClaw lacks. For personal or development use, OpenClaw alone is fine.
Yes. With local Nemotron models, NemoClaw can operate in fully air-gapped environments. This makes it suitable for government, defence, and classified workloads where data cannot leave the network.
NemoClaw is in early preview as of March 2026. It is stable for pilot and controlled deployments. General availability (GA) is expected in H2 2026. We recommend starting implementation planning now so you can go live immediately when GA drops.
For local Nemotron inference, NVIDIA recommends an RTX Pro workstation or DGX server. Smaller Nemotron models run on consumer RTX GPUs (RTX 3090 and above). For cloud-only inference (no local models), NemoClaw runs on standard x86 servers without GPU requirements.
A basic NemoClaw deployment for a small team takes 2–3 weeks. A full enterprise deployment with custom policies, multi-tenant isolation, local inference infrastructure, and compliance documentation takes 4–6 weeks. ClawConsult has delivered both — contact us for a scoped estimate.
ClawConsult specialises in NemoClaw deployments — policy design, OpenShell configuration, Nemotron inference setup, and full compliance documentation.