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
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
Fill out the form to register and to get the recording
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