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// case study — nemoclaw← all projects

NemoClaw - NVIDIA Agent Toolkit

NemoClaw is NVIDIA's answer to the enterprise adoption gap in agentic AI. It adds privacy and security controls on top of OpenClaw, the open-source OS for agentic systems. At first it looks like a security wrapper: OpenShell sandboxes the agent, Nemotron runs locally on RTX hardware, and a privacy router decides what stays on-device and what hits the cloud. But underneath, it's NVIDIA's full stack wrapped around the agentic layer - from cuDF/cuVS and vGPU for compute, to Nemotron/Nemo/Dynamo/NIM for inference, AI-Q for orchestration, and cuOPT for optimization. Announced at GTC, it represents NVIDIA's vision for enterprise-ready AI agents.

Experimental·experimentation·2024

Built in public to learn something or prove a pattern. Some are published packages, some are demos that live on this site.

// hero
nemoclaw

NemoClaw - NVIDIA Agent Toolkit

// stack
frontend
backend
PythonNVIDIA NIMNemotron
database
tools
NVIDIA RTXOpenShellcuDFcuVSvGPUAI-QcuOPT
// challenges
  • Enterprise adoption of agentic AI blocked by privacy and security concerns
  • Balancing on-device inference with cloud capabilities
  • Sandboxing autonomous agents without limiting their capabilities
// solutions
  • OpenShell sandboxes agent execution for security
  • Nemotron enables local inference on RTX hardware
  • Privacy router intelligently routes between on-device and cloud processing
// outcomes — impact2

Unlocked enterprise adoption of agentic AI with proper guardrails

Demonstrated NVIDIA's full-stack approach to the agentic layer

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