Observability

Observability for AI is the ability to understand what an AI system did, why it did it, and at what cost, by inspecting its inputs, outputs, intermediate steps, and metrics.

What is Observability?

AI observability tools capture every prompt, response, tool call, retrieval result, latency, cost, and user feedback signal, and let engineers trace a single user interaction end-to-end. Aggregate dashboards track quality, drift, cost per request, and incident counts. Observability is the precondition for evaluation, debugging, capacity planning, and regulatory evidence.

How does Observability apply to enterprise AI?

Without AI observability, an enterprise cannot answer 'why did the system give this customer that answer?'. That single question is at the heart of EU AI Act technical documentation, GDPR right-of-access, and most internal audit requests.