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

# Introducing Judges: Enhancing AI Response Quality Monitoring

> Learn how to use LaunchDarkly Judges to automatically evaluate AI model responses for relevance, accuracy, and toxicity.

> For the complete documentation index, see [llms.txt](/llms.txt). For the full documentation snapshot, see [llms-full.txt](/llms-full.txt).

<p class="publishedDate">
  <em>Published March 2, 2026</em>
</p>

<img src="https://files.buildwithfern.com/https://launchdarkly.docs.buildwithfern.com/docs/5d87741884df3be31b36bb906e1f93969a6d3adee69bca7976d3fe910247cd3b/assets/images/authors/paul-loeb.png" alt="Portrait of Paul Loeb." class="authorAvatar" />

<p class="authorName">
  by Paul Loeb
</p>

## Overview

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.

In this video, you will learn how to:

* Attach multiple judges to an AI 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](/home/ai-configs/online-evaluations)
* [Custom judges](/home/ai-configs/custom-judges)
* [Evaluate LLM Code Generation with Custom Judges and Online Evals](/tutorials/custom-evals-claude-code)