> ## Documentation Index
> Fetch the complete documentation index at: https://launchdarkly.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Introducing judges: enhancing AI response quality monitoring

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<View title="Developer" />

<View title="Federal docs" />

<View title="EU docs" />

<BlogAuthor date="March 2, 2026" avatar="/images/authors/paul-loeb.png" alt="Portrait of Paul Loeb." name="by Paul Loeb" />

Judges are a LaunchDarkly capability that automatically evaluates the responses generated by AI models in your applications. Judges score outputs based on metrics like relevance, accuracy, and toxicity, allowing you to monitor quality over time.

<Check>
  **AI Configs are called AgentControl configs**

  LaunchDarkly AI Configs have been rebranded as AgentControl and AgentControl configs. Some references in this topic may be outdated.
</Check>

In this video, you will learn how to:

* Attach multiple judges to a config
* Customize judges to fit your business needs
* Control costs by adjusting sampling percentages in different environments
* Track metrics to detect regressions and compare variations

## Introducing Judges

<iframe src="https://www.loom.com/embed/0f0e4a992df44057a31fc479acdcf032" width="560" height="315" frameborder="0" allowfullscreen />

## Learn more

* [Online evaluations](/docs/home/agentcontrol/online-evaluations)
* [Custom judges](/docs/home/agentcontrol/judges)
* [Evaluate LLM Code Generation with Custom Judges and Online Evals](/docs/tutorials/custom-evals-claude-code)