What is AI Observability?

AI observability is the ability to understand the internal behavior of AI usage from its external signals: traffic, latency, cost, model performance, policy events, and output patterns. It applies the observability discipline of modern operations to the AI layer.

Where monitoring tells you what is happening, observability lets you ask why: why did spend spike, why did a workflow’s quality drop, why is one team’s usage anomalous.

It depends on rich, structured event data from every interaction — exactly the data an AI checkpoint produces as a byproduct of supervision.

Tokto’s traffic-level records make AI usage observable by team, tool, model, provider, and policy outcome.