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  • Playbooks
    30 MIN

    Secure AI Agents with OpenShell

    Isolate OpenClaw with kernel-level policies and route inference to a local model
    Playbook
  • Healthcare & Life Sciences
    LaunchableDeveloper Example

    Ambient Healthcare Agents

    Build advanced AI agents for providers and patients using this developer example powered by NeMo Microservices, NVIDIA Nemotron, Riva ASR and TTS, and NVIDIA LLM NIM
    Blueprint
  • Playbooks
    30 MINS

    🦞 Set Up Example NemoClaw Agents 🦞

    Ready-to-run application examples for your NemoClaw sandbox — policy, prompt, and personalization for each workflow
    Playbook
  • NVIDIA
    Developer Example

    AI Factory Operations Agent

    Deploy AI agents to investigate cluster issues and streamline governed AI factory operations.
    Blueprint
  • DGX Station
    15 MIN

    DGX Station AI Skills and dgx-assist

    Inspect DGX Station software and route version-aware, CLI-backed workflows
    Playbook
  • Telecom
    LaunchableDeveloper Example

    AI Agent for Telecom Network Configuration Planning

    Automate and optimize the configuration of radio access network (RAN) parameters using agentic AI and a large language model (LLM)-driven framework.
    Blueprint
  • General
    LaunchableDeveloper Example

    NVIDIA Deep Researcher Agent

    AI agents that connect, retrieve, and reason on enterprise data—making information accessible, actionable, and intelligent.
    Blueprint
  • Playbooks
    2 HOURS

    Spark & Reachy Photo Booth

    AI augmented photo booth using the DGX Spark and Reachy Mini.
    Playbook
  • NemoClaw Icon
    NVIDIA

    NVIDIA OpenShell

    Open, secure runtime for AI agents. It governs agent execution, access, and where inference goes.
    Service
  • DGX Station
    60 MIN

    Local Healthcare Agent on DGX Station

    Run healthcare AI agents that analyze patient data and predict protein structures in an OpenShell sandbox on DGX Station
    Playbook
  • Retail
    LaunchableDeveloper Example

    Multi-Agent Intelligent Warehouse

    An AI-powered, multi-agent system designed to optimize warehouse operations through intelligent automation, real-time monitoring, and natural language interaction.
    Blueprint
  • General
    LaunchableEnterprise

    Build a Video Search and Summarization (VSS) Agent

    Ingest massive volumes of live or archived videos and extract insights for summarization and interactive Q&A
    Blueprint

  • Guides human users' AI agents to the NemoClaw docs MCP server and canonical Fern documentation in Markdown form. Use when users ask how to install, configure, operate, troubleshoot, secure, or learn NemoClaw with an AI coding assistant. Trigger keywords -
    Skill
  • Playbooks
    30 MIN

    Run OpenClaw with a Local LLM

    Install a local-first AI agent and connect it to a private OpenAI-compatible model endpoint
    Playbook

  • Build, migrate, review, and maintain third-party NVIDIA NeMo Fabric adapters against the public adapter contract. Use when creating adapter or target descriptors, mapping AgentConfig into an agent harness or custom-agent runtime, implementing start/invoke
    Skill

  • Use for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.
    Skill

  • How to swap the VLM in the VSS Alerts Blueprint — covers RTVI-VLM microservice deployment methods, all three VLM consumers (rtvi-vlm, vlm-as-verifier, vss-agent), and health checks.
    Skill

  • Run a TAO training/evaluation/inference container on an NVIDIA Brev GPU instance. Instance provisioning (create/search/stop/delete/login) is delegated to the official brev-cli agent skill or the Brev MCP server; this skill covers only the TAO-specific par
    Skill
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