# Google Vertex AI
**Supported Labeling Types**: `Row labeling`
We have made it easy for you to connect our system with [**Vertex AI**](https://cloud.google.com/vertex-ai). If you already have data and training pipelines in Vertex AI, you can use your trained model to improve it.
### Extension Menu
To use the Vertex AI model, you must select Google Vertex AI in the Settings option. Once selected, you will see the following menu.
ML-assisted labeling with Google Vertex AI
1. **Target text**: Pick which text to use as input for reference.
2. **Target question**: Decide which output column to predict.
3. **API URL**: The endpoint from Google Vertex AI. The format will follow the sample below:
`https://-aiplatform.googleapis.com/ui/projects//locations//endpoints/:predict`
4. **Faster prediction speed**: Toggle this option to run predictions faster via the backend.
### Setup Your Model
You can view the endpoint URL by clicking on the endpoint's name after the successful deployment.
Endpoint page from Google Vertex AI
To allow **ML-assisted labeling** to run your model, you need to grant access Datasaur Service Account as Vertex AI Administrator. Below are the steps:
1. Navigate to your selected project where your model is located.
2. Go to **IAM & Admin**.
3. Click on the **IAM** option in the left sidebar.
IAM page menu
4. Click **Grant Access**.
5. In the **New Principals** field, fill in the **Service Account Email**:
Grant access to the selected project
6. In the role field, select **Vertex AI Administrator**.
7. Click **Save** to finish setting up permissions.
### Use the Model in ML-Assisted Labeling
After configuring all the settings above, you can copy the endpoint URL and paste it into the API URL field. You can predict the labels and obtain the predicted labels from your own model by clicking **Predict labels**.
