# Evals

Evals are structured tests that measure whether an AI system performs a task accurately, safely, and consistently.

## Why it matters

Evals turn “it seems good” into repeatable evidence. A useful evaluation set reflects real tasks and failure modes, uses explicit graders, records baselines, and runs again when prompts, models, tools, or policies change.

## Example

Before releasing a support agent, a team tests 200 anonymized cases for correct resolution, citation quality, unsafe disclosure, escalation behavior, latency, and cost.

## FAQ

### What is Evals in simple terms?

Evals are structured tests that measure whether an AI system performs a task accurately, safely, and consistently.

### Why does Evals matter for teams using AI?

Evals turn “it seems good” into repeatable evidence. A useful evaluation set reflects real tasks and failure modes, uses explicit graders, records baselines, and runs again when prompts, models, tools, or policies change.

### What is a practical example of Evals?

Before releasing a support agent, a team tests 200 anonymized cases for correct resolution, citation quality, unsafe disclosure, escalation behavior, latency, and cost.


Source: https://www.luffy.so/ai-glossary/evals

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