How to connect Google Vertex AI and AI Agent
Create a New Scenario to Connect Google Vertex AI and AI Agent
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 AI Agent will be your first step. To do this, click "Choose an app," find Google Vertex AI or AI Agent, 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 AI Agent Node
Next, click the plus (+) icon on the Google Vertex AI node, select AI Agent from the list of available apps, and choose the action you need from the list of nodes within AI Agent.

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Authenticate AI Agent
Now, click the AI Agent node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your AI Agent settings. Authentication allows you to use AI Agent through Latenode.
Configure the Google Vertex AI and AI Agent 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 AI Agent 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Vertex AI, AI Agent, 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 AI Agent integration works as expected. Depending on your setup, data should flow between Google Vertex AI and AI Agent (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 AI Agent
Google Sheets + Google Vertex AI + AI Agent: When a new row is added to a Google Sheet, the data is sent to Vertex AI for sentiment analysis. The AI Agent then summarizes the sentiment and stores the summary back into the Google Sheet as a comment.
AI Agent + Google Vertex AI + Slack: The AI agent flags urgent customer requests. Vertex AI analyzes the sentiment of those requests. If the sentiment is negative, a notification is sent to a support team channel in Slack.
Google Vertex AI and AI Agent 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 AI Agent
Use AI Agent in Latenode to automate content creation, data analysis, or customer support. Configure agents with prompts, then integrate them into workflows. Unlike standalone solutions, Latenode lets you connect AI to any app, scale automatically, and customize with code where needed.
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See how Latenode works
FAQ Google Vertex AI and AI Agent
How can I connect my Google Vertex AI account to AI Agent using Latenode?
To connect your Google Vertex AI account to AI Agent 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 AI Agent accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate content creation using AI Agent and Vertex AI?
Yes, Latenode enables seamless content automation using AI Agent and Vertex AI. Generate marketing copy, blog posts, and more, leveraging Latenode's visual editor for advanced logic control.
What types of tasks can I perform by integrating Google Vertex AI with AI Agent?
Integrating Google Vertex AI with AI Agent allows you to perform various tasks, including:
- Automating customer service chatbot responses using AI Agent.
- Analyzing customer sentiment from chat logs via Vertex AI's NLP.
- Generating personalized email marketing campaigns via AI Agent.
- Training custom AI models for specific Agent tasks on Vertex AI.
- Extracting structured data from unstructured text in AI Agent responses.
HowdoImanageGoogleVertexAIAPIkeyssecurelyinLatenode?
Latenode provides secure storage for API keys. Use environment variables to protect your Google Vertex AI credentials, ensuring they are never exposed in your workflows.
Are there any limitations to the Google Vertex AI and AI Agent integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations might require JavaScript code blocks.
- Real-time data synchronization depends on the API rate limits of both services.
- Very large file processing may require optimization for optimal performance.