NodeLoom is the control plane for AI agents in production. Discover every agent across your environment, monitor behavior against baselines, and govern with cryptographic audit trails. Detect token spikes, data exfiltration, and behavioral drift. Generate compliance reports for SOC 2, ISO 42001, NIST AI RMF, GDPR, HIPAA, and SOX mapped to actual agent behavior. SDKs in Python, TypeScript, Java, and Go.

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Hey Product Hunt!

I’m Reda. I spent 15+ years building enterprise security infrastructure and kept running into the same gap: teams shipping AI agents into production with no visibility into what those agents actually do at runtime.

No monitoring. No guardrails. No audit trail. And when an agent goes off-script or makes unauthorized tool calls, you’re scrambling.

That’s why I built NodeLoom:

∙ SDKs in Python, TypeScript, Java, and Go so you instrument existing agents without migrating to a new orchestration layer

∙ Real-time behavioral monitoring and drift detection

∙ Runtime guardrails that enforce policies before agents act

∙ Cryptographic audit trails for every agent decision

∙ Automated compliance reporting for SOC 2, HIPAA, GDPR, SOX, and PCI

Drop in a few lines of code and get full observability and governance over your entire agent fleet.

I’m actively looking for design partners, especially teams running agents in regulated environments or anyone who’s been burned by an agent going off-script in production.

Try it at nodeloom.io or ask me anything here. I read and reply to everything.

Been following the agentic AI security space closely, and NodeLoom is tackling something most teams are just starting to feel the pain of. Once you move beyond single-agent prototypes into multi-agent production systems, observability and access governance become a real gap. The demo shows exactly the use cases I’ve kept bumping into with customers. Excited to see where this goes.

@sebastian_martinez06 I have built NodeLoom for these exact reasons, thank you glad that the demo resinated!