Building More Secure Autonomous AI Agents with NVIDIA NemoClaw
Most enterprise GenAI projects stall at the same gate: security review. NemoClaw — an open source blueprint for building safer autonomous agents — was built to close that gap, wrapping OpenClaw with a kernel-level sandbox, an L7 egress proxy, and an intent-classifying policy engine.
In this live, demo-focused session, we'll show two ways to run NemoClaw on Nebius: connect it to Nebius Token Factory inference in minutes, then deploy it end-to-end on Nebius Serverless GPU — driven by a single agent prompt.
In this webinar, you'll learn how to:
Deploy a sandboxed AI agent on Nebius in under 15 minutes using NemoClaw, OpenClaw, and Token Factory inference
Stop prompt injection, data exfiltration, and tool misuse with OpenShell's L7 proxy and policy engine before they reach your model
Wire NemoClaw to Nebius Token Factory for OpenAI-compatible inference across DeepSeek-V3.2, Llama-3.3-70B, and Hermes-4-70B
Spin up the full NemoClaw stack on Nebius Serverless GPU with a single natural-language prompt and a local NIM for in-VPC inference
Apply production-tested patterns for shipping enterprise AI agents safely, plus the bugs we hit and filed publicly with NVIDIA and Nebius
Walk away with a working tutorial repo you can clone, configure, and run against your own Nebius account the same day
Who should attend
Mid-size and enterprise companies exploring long-running AI agents like OpenClaw for enterprise use
AI, platform, and security teams evaluating how to deploy autonomous agents safely in production
Engineering leaders building enterprise GenAI systems with secure tool use, auditability, and governance requirements
Speakers
Colin Lowenberg - Developer Relations, Nebius
Sam Pastoriza - Solution Architect, NVIDIA