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

# Case Study

> Design and evaluate real-world work simulations.

## Overview

Case Studies allow you to evaluate candidates through realistic work simulations. Whether it's a coding challenge, a marketing strategy, or a design task, Case Studies provide deep insights into a candidate's problem-solving abilities and practical skills.

## Creating a Case Study

Navigate to the **Assessments** tab on the left sidebar and select **Case Study**.

<Tabs>
  <Tab title="ATS Integration">
    Generate a case study directly from a job posting.

    <Steps>
      <Step title="Select Source">
        Click **New** and select **From Job Posting**.
      </Step>

      <Step title="Choose Job">
        Select the relevant job posting from your connected ATS.
      </Step>

      <Step title="Create">
        Casuro will analyze the job requirements and generate a relevant case study draft.
      </Step>
    </Steps>
  </Tab>

  <Tab title="AI Prompt">
    Describe what you want to test, and let our AI build it for you.

    <Steps>
      <Step title="Describe">
        Enter a prompt describing the role and the skills you want to evaluate (e.g., "Senior Product Manager focusing on growth metrics").
      </Step>

      <Step title="Generate">
        Our AI will construct a complete case study scenario tailored to your description.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Standalone">
    Start with a blank document.

    <Steps>
      <Step title="Select Template">
        Click **New** and select **Blank Template**.
      </Step>

      <Step title="Build">
        Use the editor to manually structure your case study from the ground up.
      </Step>
    </Steps>
  </Tab>
</Tabs>

## Configuring the Case Study

Our platform features a **state-of-the-art editor** designed to streamline the creation process.

### Agent-Enabled Editor

The editor is powered by a **context-aware AI agent** that acts as your co-pilot.

* **Content Creation**: Ask the agent to draft sections, scenarios, or instructions.
* **Research**: The agent can perform research to ensure your case study is grounded in current industry standards and real-world data.
* **Refinement**: Use the agent to polish your language or adjust the difficulty level.

### Actions

* **Job Attachment**: Link the case study to a specific job for better tracking.
* **Panel**: Assign team members to review and grade the submissions.
* **Launch**: Publish the case study to start sending invites.
* **Rubrics**: Define clear success criteria. You can manually input rubrics or ask the AI agent to generate them based on the case study content and the target role.

## Inviting Candidates

Once launched, your Case Study moves to the **Launchpad**.

<Tabs>
  <Tab title="Manual Invite">
    Go to the **Invite** tab in the launchpad to send individual invitations via email.
  </Tab>

  <Tab title="ATS Automation">
    Configure workflows to automatically invite candidates when they reach a specific stage in your ATS.

    <Note>
      See our [Integration Guides](/integrations) for details on setting up automation.
    </Note>
  </Tab>
</Tabs>

## Candidate Experience

Candidates receive a secure link to a dedicated workspace where they can:

* **Review Materials**: Access all case documents and instructions.
* **Submit Work**: Upload files, write code, or record video responses depending on the case requirements.
* **Simulate Real Work**: Experience a realistic preview of the role.

## Evaluation & Results

Submissions are evaluated against your defined rubrics.

**What you get:**

* **AI Analysis**: Preliminary scoring and insights generated by our AI.
* **Rubric Scoring**: A structured breakdown of performance against each criterion.
* **Reviewer Feedback**: Tools for your hiring panel to leave comments and final grades.