Testing vs. observability vs. guardrails

AI testing is a methodology applied at a defined point: structured assessment against a golden dataset, before you ship.

AI observability (Arize, WhyLabs, Helicone, Datadog) is runtime monitoring of production traffic. AI eval platforms (Braintrust, Galileo, LangSmith) are SaaS dashboards for managing test runs over time. AI guardrails (Lakera, NeMo, Patronus) are runtime filters that block bad outputs before they reach users.

They complement rather than replace each other — but only testing tells you, before deploy, whether the system is right.