# Amazon SageMaker **Supported Labeling Types**: `Row labeling` Integrate your Amazon SageMaker Inference Endpoint effortlessly with Datasaur. Utilize Datasaur's **ML-assisted labeling** to access and leverage your deployed Amazon SageMaker Inference Endpoint for data labeling. ## Setup Datasaur ML Assisted Extension {% hint style="info" %} Please ensure you have access to our **ML-assisted labeling** extension with Amazon SageMaker as a provider. {% endhint %} 1. [Create a custom project ](https://datasaurai.gitbook.io/datasaur/nlp-projects/creating-a-project)for row labeling 2. Click the gear icon from the extension panel to open the **Manage extensions** dialog. 3. Enable the **ML-assisted labeling** extension.

Image of Manage Extension Pop Up to enable ML assisted — Manage Extension Pop Up

4. **ML-assisted labeling** is now enabled. Select Amazon SageMaker as the provider.

Image of ML Assisted with Amazon SageMaker — **ML-assisted labeling** with Amazon SageMaker

## Setup Role in AWS Identity and Access Management (IAM) Before we start to create Role in the **IAM** page, please create these policies first for your permissions when creating a new Role. 1. Go to your **IAM** page, navigate to the **Policies** section, and then create a new policy. 2. You can download the examples below. {% file src="" %} Now you can continue to create a new Role with the policy. 1. Go to the **IAM** page and navigate to the **Roles** section 2. Click on **Create Roles** then select **AWS account** as the role type and insert the **Account ID** and **External ID**. These values are automatically generated within the **ML-assisted labeling** extension and can be copied and pasted into the AWS platform.

Image of Select trusted entity menu — Select trusted entity

3. On the **Add permissions** step, search the policy you created before. Add them to the permissions. 4. Provide a role name and click **Create role** and you can check the trusted policies config below {% file src="" %} 5. The role will be created successfully. 6. View your role and copy the Role ARN.

7. Paste this information into the **ML-assisted labeling** extension. 8. Navigate to the Amazon SageMaker page and retrieve the Endpoint ARN. Copy the obtained Endpoint ARN and paste it into the extension.

Image of Endpoint Details — Endpoint details

## Start Prediction After setting up the above options, simply click **Predict labels** to start predicting and obtaining labels from your Amazon SageMaker endpoint.

Image of Prediction result — Prediction appears

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