/* Adjust space between sidebar sections */
.sidebar > .section {
    margin-bottom: 0px; /* Adjust spacing as needed */
  }
  
  /* Adjust space between pages within a section */
  .sidebar .page {
    margin-bottom: 0px; /* Adjust spacing as needed */
  }

  /* Adjust padding inside each page link */
.sidebar .page a {
    padding: 0px 0px; /* Adjust top/bottom and left/right padding */
  }
  
  /* Section highlight animation when targeted through anchor links */
  :target,
  h2[id]:target,
  h3[id]:target,
  h4[id]:target,
  h5[id]:target,
  div[id]:target {
    position: relative;
    background: linear-gradient(to left, #e9b405, #2b2a2a00);
    animation: highlight-section 3s ease-in-out;
    scroll-margin-top: 80px;
    padding: 0.2rem;
    border-radius: 8px;
    border-left: 4px solid #f2ca46;
  }
  
  @keyframes highlight-section {
    0% {
      background: linear-gradient(to left, #e9b405, #2b2a2a00);
    }
    50% {
      background: linear-gradient(to left, #e9b405, #2b2a2a00);
    }
    100% {
      background: linear-gradient(to left, #e9b405, #2b2a2a00);
    }
  }

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DeepRails Overview

Learn why LLM-as-a-Judge is the new gold standard for evaluating AI responses

LLM Evaluations

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Quickstart Guide

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Monitor Overview

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Defend Overview

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HyperChainpoll

How DeepRails aggregates granular evaluations into actionable scores

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Explore DeepRails Guardrail metrics designed to evaluate LLM behavior.

Metrics Comparison

Evaluate factual accuracy in AI outputs using DeepRails Guardrail Metrics to detect and prevent hallucinations in your AI systems.

Correctness

Evaluate whether AI responses thoroughly and accurately address all aspects of a user's query using DeepRails Guardrail Metrics.

Completeness

Evaluate the safety of AI-generated content using DeepRails Guardrail Metrics to identify and mitigate harmful or high-risk responses.

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