> For the complete documentation index, see [llms.txt](https://docs.datasaur.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datasaur.ai/integrations/webhook-notifications.md).

# Webhook Notifications

## Receive notifications via webhook

Datasaur provides webhooks to notify your application when an event happens in your labeling projects. Webhooks are useful for automation in your machine learning projects. For example, you can use a webhook to feed the data directly into your model right after labelers complete their projects.

To start using webhooks, follow these steps below.

1. Create a webhook endpoint on your server.
2. Register the endpoint with Datasaur. For this you will need to contact <support@datasaur.ai>.

### List of events

Datasaur provides a number of events that you can listen to and leverage.

* **Project created:** This event will be triggered when a new project is created.
* **Before update labels:** This event will be triggered just before the labeler apply a new label or update an existing label.
* **Project completed:** This event will be triggered when a labeler marks the project as complete in the labeler mode.
* **Project reviewed:** This event will be triggered when a reviewer marks the project as complete in reviewer mode.


---

# 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 dynamically by asking a question.

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

```
GET https://docs.datasaur.ai/integrations/webhook-notifications.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.
