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----
-title: ArangoGraph Notebooks
-menuTitle: ArangoGraph Notebooks
-weight: 130
-description: >-
-  Colocated Jupyter Notebooks within the ArangoGraph Insights Platform
----
-{{< tip >}}
-ArangoGraph Notebooks don't include the ArangoGraphML services.
-To enable the ArangoGraphML services, 
-[get in touch](https://www.arangodb.com/contact/)
-with the ArangoDB team.
-{{< /tip >}}
-
-The ArangoGraph Notebook is a JupyterLab notebook embedded in the
-[ArangoGraph Insights Platform](https://dashboard.arangodb.cloud/home?utm_source=docs&utm_medium=cluster_pages&utm_campaign=docs_traffic).
-The notebook integrates seamlessly with the platform,
-automatically connecting to ArangoGraph services and ArangoDB.
-This makes it much easier to leverage these resources without having
-to download any data locally or to remember user IDs, passwords, and endpoint URLs.
-
-For more information, see the [Notebooks](../arangograph/notebooks.md) documentation.
diff --git a/site/content/3.13/data-science/notebook-servers.md b/site/content/3.13/data-science/notebook-servers.md
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+---
+title: Notebook Servers
+menuTitle: Notebook Servers
+weight: 130
+description: >-
+  Colocated Jupyter Notebooks within the ArangoDB Platform
+aliases:
+  - data-science/arangograph-notebooks
+---
+
+{{< tag "ArangoDB Platform" >}}
+
+ArangoDB Notebooks provide a Python-based, Jupyter-compatible interface for building
+and experimenting with graph-powered data, GenAI, and graph machine learning
+workflows directly connected to ArangoDB databases. The notebook servers are
+embedded in the ArangoGraph ecosystem and offer a
+pre-configured environment where everything, including all the necessary services
+and configurations, comes preloaded. You don't need to set up or configure the
+infrastructure, and can immediately start using the GraphML and GenAI
+functionalities.
+
+The notebooks are primarily focused on the following solutions:
+- **GraphRAG**: A complete solution for extracting entities
+  from text files to create a knowledge graph that you can then query with a
+  natural language interface.
+- **GraphML**: Apply machine learning to graphs for link prediction,
+  classification, and similar tasks.
+- **Integrations** : Use ArangoDB together with cuGraph, NetworkX, and other data science tools.
+
+<!-- TODO: Add links to corresponding pages -->
+
+The ArangoDB Notebooks also include the following services and tools:
+- Automatically connect to ArangoDB databases and GenAI platform services
+- [Magic commands](../arangograph/notebooks.md#arangograph-magic-commands)
+  that simplify database interactions
+- [ArangoDB CLI Tools](../components/tools/) included in each Notebook server
+  to interact with ArangoDB from the command line  
+
+## Quickstart
+
+1. In the ArangoDB Platform web interface, select a database.
+2. Under **GenAI Tools**, click **Notebook servers**.
+3. The **Notebook servers** page displays an overview of the notebook services. Click
+  **New notebook server** to create a new one.
+4. After your notebook service is launched, you can start interacting with the
+  Jupyter interface.
+
+{{< tip >}}
+To get a better understanding of how to interact with ArangoDB, use
+the `GettingStarted.ipynb` template from the file browser.
+{{< /tip >}}
+
+<!-- TODO: Add links to interactive tutorials? -->
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