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

# Human Reviews

> Grade AI traces against a shared rubric and turn expert judgment into reusable memory.

Human Reviews is where your experts grade individual AI traces. A **review** is one expert's grading of one trace: a score on each dimension of a rubric, a short rationale, and, when the answer was wrong, a corrected answer.

Captured as structured data instead of scattered across Slack threads and spreadsheets, that judgment can train your [judges](/docs/judges/overview) and speed up later reviews.

## How a review flows

<Steps>
  <Step title="Define the standard">
    Under **Rubrics**, an admin sets what to grade and what "good" looks like. See [Rubrics](/docs/reviews/rubric-studio).
  </Step>

  <Step title="Route traces to reviewers">
    Send traces to a **queue**, which spreads them across a team, or hand them to specific people. See [Queues & Reviews](/docs/reviews/operational-loop).
  </Step>

  <Step title="Grade">
    Each reviewer works through their own list, with the [Review Copilot](/docs/reviews/copilot) drafting rationales and corrections for them to check.
  </Step>

  <Step title="Reuse the results">
    See where reviewers agreed, calibrate a judge against their grades, and turn corrected traces into datasets.
  </Step>
</Steps>


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