LLM Status vs Nano

Track where every AI model is used across your apps, and get warned before one is deprecated or retired.

An AI-native security and observability platform for cloud, local, hybrid, and air-gapped teams. Sub-second search, detection engineering, OpenTelemetry, pivt AI, and...

About LLM Status

Track where every AI model is used across your apps, and get warned before one is deprecated or retired. Run mm for the full terminal dashboard: it scans the current repo on launch, then you arrow through every model it calls, browse the registry, and see what's new, live. Both pull the signed registry from cdn.llmstatus.ai once, then run offline. The Here and What's New tabs read straight off the signed registry, no account, works offline.

About Nano

An AI-native security and observability platform for cloud, local, hybrid, and air-gapped teams. Sub-second search, detection engineering, OpenTelemetry, pivt AI, and deployment control in one place. Run nano in the cloud, locally, hybrid, or air-gapped. nano was built from scratch, not refactored: a dedicated cluster, one query language over your security and OpenTelemetry data, agentic investigation, and deployment options from cloud to air-gapped. So when a service slows down, "is this an outage or a breach?" is one query, not two tools and a guess.