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

# Introduction

Building reliable LLM applications means knowing whether a new prompt, model, or change of flow actually makes things better.

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  <img className="hidden dark:block" src="https://mintcdn.com/enrolla-nk-hub-guardrails/MnHRGhi6rxtiPuOU/img/experiment/exp-list-dark.png?fit=max&auto=format&n=MnHRGhi6rxtiPuOU&q=85&s=5821f5e6436d56473c286326d00b7964" width="3266" height="492" data-path="img/experiment/exp-list-dark.png" />
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Experiments in Traceloop provide teams with a structured workflow for testing and comparing results across different prompt, model, and evaluator checks, all against real datasets.

## What You Can Do with Experiments

<CardGroup cols={2}>
  <Card title="Run Multiple Evaluators" icon="list-check">
    Execute multiple evaluation checks against your dataset
  </Card>

  <Card title="View Complete Results" icon="table">
    See all experiment run outputs in a comprehensive table view with relevant indicators and detailed reasoning
  </Card>

  <Card title="Compare Experiment Runs Results" icon="code-compare">
    Run the same experiment across different dataset versions to see how it affects your workflow
  </Card>

  <Card title="Custom Task Pipelines" icon="code">
    Add a tailored task to the experiment to create evaluator input. For example: LLM calls, semantic search, etc.
  </Card>
</CardGroup>