How to connect Google Vertex AI and Pinterest
Create a New Scenario to Connect Google Vertex AI and Pinterest
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Vertex AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Vertex AI or Pinterest will be your first step. To do this, click "Choose an app," find Google Vertex AI or Pinterest, and select the appropriate trigger to start the scenario.

Add the Google Vertex AI Node
Select the Google Vertex AI node from the app selection panel on the right.

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Configure the Google Vertex AI
Click on the Google Vertex AI node to configure it. You can modify the Google Vertex AI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Pinterest Node
Next, click the plus (+) icon on the Google Vertex AI node, select Pinterest from the list of available apps, and choose the action you need from the list of nodes within Pinterest.

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Authenticate Pinterest
Now, click the Pinterest node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Pinterest settings. Authentication allows you to use Pinterest through Latenode.
Configure the Google Vertex AI and Pinterest Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Vertex AI and Pinterest Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Vertex AI, Pinterest, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Vertex AI and Pinterest integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Pinterest (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Vertex AI and Pinterest
Pinterest + Google Vertex AI + Canva: When a new pin is created on Pinterest, its details are sent to Google Vertex AI for analysis. Based on the AI's analysis, Canva creates an ad creative.
Pinterest + Google Vertex AI + Shopify: When a new pin is created on Pinterest, its data is sent to Google Vertex AI for analysis using Gemini. Then, Shopify updates the product description based on the insights from Google Vertex AI.
Google Vertex AI and Pinterest integration alternatives
About Google Vertex AI
Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.
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About Pinterest
Automate Pinterest tasks within Latenode. Pin, repin, and manage boards based on triggers from other apps. Automate content curation, schedule pins, and track performance—all inside your workflows. Connect Pinterest to your marketing stack, enrich data, and scale your campaigns without code.
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FAQ Google Vertex AI and Pinterest
How can I connect my Google Vertex AI account to Pinterest using Latenode?
To connect your Google Vertex AI account to Pinterest on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Vertex AI and click on "Connect".
- Authenticate your Google Vertex AI and Pinterest accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically post AI-generated Pinterest ads?
Yes, you can! Latenode lets you use Google Vertex AI to generate ad copy and images, then automatically post them to Pinterest. Scale your campaigns with no-code ease.
What types of tasks can I perform by integrating Google Vertex AI with Pinterest?
Integrating Google Vertex AI with Pinterest allows you to perform various tasks, including:
- Automatically generate Pinterest ad copy with Vertex AI's language models.
- Use Vertex AI Vision to identify trending visual elements for Pins.
- Personalize Pinterest recommendations based on Vertex AI-analyzed user data.
- Create dynamic Pinterest boards populated with AI-generated content.
- Analyze Pinterest engagement metrics using Vertex AI for campaign optimization.
Can Latenode workflows process large Google Vertex AI datasets?
Yes, Latenode efficiently handles large Google Vertex AI datasets using its scalable architecture, enabling complex analysis and automation without performance bottlenecks.
Are there any limitations to the Google Vertex AI and Pinterest integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by the Google Vertex AI and Pinterest APIs may affect high-volume workflows.
- Complex AI model deployments within Latenode require appropriate Google Vertex AI resource allocation.
- Custom JavaScript code might be necessary for advanced data transformations beyond no-code blocks.