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

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Wachete
Authenticate Wachete
Now, click the Wachete node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Wachete settings. Authentication allows you to use Wachete through Latenode.
Configure the Google Vertex AI and Wachete 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 Wachete 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.

JavaScript
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AI Anthropic Claude 3
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Wachete
Trigger on Webhook
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Google Vertex AI
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Google Vertex AI, Wachete, 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 Wachete integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Wachete (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 Wachete
Wachete + Google Vertex AI + Slack: When Wachete detects a change on a monitored webpage, it triggers Vertex AI to analyze the new content's sentiment. A message containing the sentiment analysis is then sent to a Slack channel.
Wachete + Google Vertex AI + Google Sheets: When Wachete detects changes on a monitored website, Vertex AI analyzes the text for sentiment. The text and the sentiment score are then logged into a Google Sheet.
Google Vertex AI and Wachete 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 Wachete
Use Wachete in Latenode to monitor website changes and trigger automated actions. Get notified of price drops, content updates, or competitor activity, then use Latenode to update databases, send alerts, or adjust strategies – all visually. Automate critical responses faster than ever.
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See how Latenode works
FAQ Google Vertex AI and Wachete
How can I connect my Google Vertex AI account to Wachete using Latenode?
To connect your Google Vertex AI account to Wachete 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 Wachete accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze website changes using Vertex AI via Wachete?
Yes, you can! Latenode's visual editor simplifies sending Wachete's data to Vertex AI for analysis. Gain deeper insights into content shifts without complex coding, powered by AI.
What types of tasks can I perform by integrating Google Vertex AI with Wachete?
Integrating Google Vertex AI with Wachete allows you to perform various tasks, including:
- Monitor competitor website content and analyze changes with Vertex AI models.
- Automatically detect and classify new products added to e-commerce sites.
- Track sentiment changes on news articles and summarize key updates.
- Analyze changes in job postings to identify emerging skill requirements.
- Automate content quality checks using AI on newly published web pages.
How does Latenode enhance Google Vertex AI integration?
Latenode simplifies Vertex AI workflows using a visual builder. Combine AI with other tools and logic without coding for powerful automation.
Are there any limitations to the Google Vertex AI and Wachete integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex AI model deployments in Vertex AI might require custom JavaScript.
- Wachete's free plan limitations will affect data available for Vertex AI analysis.
- High-volume data processing may require optimizing Latenode workflow performance.