# How it works

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This page was generated from content adapted from the [AWS Developer Guide](https://github.com/awsdocs/amazon-rekognition-developer-guide.git)
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## Types of analysis

* **Note**\
  For information about Amazon Rekognition Custom Labels, see the [Amazon Rekognition Custom Labels Developer Guide](https://docs.aws.amazon.com/rekognition/latest/customlabels-dg/what-is.html).

## Non-storage and storage API operations

* **Note**\
  The service does not persist actual image bytes. Instead, the underlying detection algorithm first detects the faces in the input image, extracts facial features into a feature vector for each face, and then stores it in the database. Amazon Rekognition uses these feature vectors when performing face matches.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://awsnotes.dendron.so/machine-learning/amazon-rekognition/topics/how-it-works.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.