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

# Build Anomaly Detection Models

export const vp = 'Visual Prompting';

export const smartLabel = 'Smart Labeling';

export const productLL = 'LandingLens';

export const mi = 'Mobile Inference';

export const llsf = 'LandingLens on Snowflake';

export const companyName = 'LandingAI';

*This article applies to these versions of LandingLens:*

<table>
  <thead>
    <tr>
      <th>LandingLens</th>
      <th>LandingLens on Snowflake</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td><span class="check-icon">✓</span></td>
      <td><span class="check-icon">✓</span></td>
    </tr>
  </tbody>
</table>

<iframe width="560" height="315" src="https://www.youtube.com/embed/i-FGSp0V5Y8?&wmode=opaque&rel=0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen />

Use LandingLens to develop [Anomaly Detection](/anomaly-detection) models! The ability to create Anomaly Detection models enables your organization to detect visual deviations and irregularities—with few images of defects upfront.

Whether monitoring quality on a production line, identifying out-of-place items in a warehouse, or flagging visual inconsistencies in your digital workflows, Anomaly Detection helps uncover what doesn’t belong—before it becomes a business issue.

Watch this video tutorial to learn:

* What an Anomaly Detection model is
* How to classify images as Normal or Abnormal at upload
* What images LandingLens uses to train models
* How to use heatmaps to understand model predictions