How to connect Google Vertex AI and Data Enrichment
Create a New Scenario to Connect Google Vertex AI and Data Enrichment
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 Data Enrichment will be your first step. To do this, click "Choose an app," find Google Vertex AI or Data Enrichment, 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.

Google Vertex AI
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 Data Enrichment Node
Next, click the plus (+) icon on the Google Vertex AI node, select Data Enrichment from the list of available apps, and choose the action you need from the list of nodes within Data Enrichment.

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Data Enrichment
Authenticate Data Enrichment
Now, click the Data Enrichment node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Data Enrichment settings. Authentication allows you to use Data Enrichment through Latenode.
Configure the Google Vertex AI and Data Enrichment 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 Data Enrichment 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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AI Anthropic Claude 3
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Data Enrichment
Trigger on Webhook
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Google Vertex AI
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Webhook response
Save and Activate the Scenario
After configuring Google Vertex AI, Data Enrichment, 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 Data Enrichment integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Data Enrichment (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 Data Enrichment
Data Enrichment + Google Vertex AI + Salesforce: When a new lead is created in Salesforce, the lead data is enriched using Data Enrichment. Then, Google Vertex AI analyzes the enriched data to generate insights. Finally, the lead record in Salesforce is updated with these AI-powered insights.
Data Enrichment + Google Vertex AI + Google Sheets: When a new row is added to Google Sheets, customer profile data in that row is enriched using Data Enrichment. Google Vertex AI analyzes the enriched data to provide insights. The results are then updated in the same Google Sheets row.
Google Vertex AI and Data Enrichment 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 Data Enrichment
Enrich lead data, verify addresses, or flag fraud risks within Latenode workflows. Connect Data Enrichment APIs to auto-update records across apps. Streamline data cleaning and validation with no-code blocks or custom JS. Automate tasks that need enhanced data for better decisions, at scale.
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FAQ Google Vertex AI and Data Enrichment
How can I connect my Google Vertex AI account to Data Enrichment using Latenode?
To connect your Google Vertex AI account to Data Enrichment 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 Data Enrichment accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I enrich AI-generated content with user data?
Yes, you can. Latenode’s visual editor simplifies enriching Google Vertex AI content with Data Enrichment, ensuring personalized, context-aware outputs. Refine AI responses with rich data.
What types of tasks can I perform by integrating Google Vertex AI with Data Enrichment?
Integrating Google Vertex AI with Data Enrichment allows you to perform various tasks, including:
- Enhancing AI model outputs with demographic data for targeted results.
- Automating lead scoring based on AI-driven insights and enriched profiles.
- Personalizing customer experiences by enriching AI-generated content.
- Analyzing sentiment in enriched text data for improved understanding.
- Creating AI-powered reports with comprehensive, enriched information.
How does Latenode handle large data volumes for Google Vertex AI?
Latenode's architecture efficiently manages large datasets for Google Vertex AI, enabling scalable AI workflows without performance bottlenecks.
Are there any limitations to the Google Vertex AI and Data Enrichment integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations may require custom JavaScript code.
- Rate limits of Google Vertex AI and Data Enrichment apply.
- Integration performance depends on the size and complexity of data processed.