> For the complete documentation index, see [llms.txt](https://docs.umbraco.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.umbraco.com/ai-in-umbraco/19.latest/management-api/extraction.md).

# Extraction

REST API endpoint for extracting typed values from text (experimental).

{% hint style="warning" %}
Extraction is **experimental**. When the `Umbraco:AI:Experimental:Extraction` feature flag is disabled, these endpoints return **404** with an empty body. See [Enabling Extraction](/ai-in-umbraco/19.latest/using-the-api/extraction.md#enabling-extraction).
{% endhint %}

The Extraction API reads typed values out of a piece of text using an Extraction profile. One call can extract multiple fields, and they are all answered in a single model call.

## Base URL

```
/umbraco/ai/management/api/v1/extraction
```

## Authentication

The endpoint requires an authenticated backoffice user (policy: `BackOfficeAccess`). Access to the AI section is not required, so backoffice extensions outside the AI section can call it. See [Authentication](/ai-in-umbraco/19.latest/management-api/management-api/authentication.md).

## Endpoints

| Method | Endpoint                                           | Description                                                                     |
| ------ | -------------------------------------------------- | ------------------------------------------------------------------------------- |
| POST   | `/umbraco/ai/management/api/v1/extraction/extract` | [Extract values](/ai-in-umbraco/19.latest/management-api/extraction/extract.md) |

## Checking Whether Extraction Is Enabled

To check whether Extraction is enabled before you call it, use the `GET /umbraco/ai/management/api/v1/capabilities/enabled` endpoint. The response includes `"Extraction"` only when the feature flag is on. Unlike the Extraction endpoint, that endpoint requires access to the AI section. See [List Capabilities](/ai-in-umbraco/19.latest/management-api/connections/capabilities.md#list-enabled-capabilities).

## In This Section

{% content-ref url="/pages/Njt6E4JJDpRakq6RdoQ0" %}
[Extract Values](/ai-in-umbraco/19.latest/management-api/extraction/extract.md)
{% endcontent-ref %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.umbraco.com/ai-in-umbraco/19.latest/management-api/extraction.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.
