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

Google Vertex AI
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WhatConverts

Authenticate WhatConverts
Now, click the WhatConverts node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your WhatConverts settings. Authentication allows you to use WhatConverts through Latenode.
Configure the Google Vertex AI and WhatConverts 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 WhatConverts 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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WhatConverts
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, WhatConverts, 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 WhatConverts integration works as expected. Depending on your setup, data should flow between Google Vertex AI and WhatConverts (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 WhatConverts
WhatConverts + Google Vertex AI + Google Sheets: When a new lead is captured in WhatConverts, its details are sent to Google Vertex AI for sentiment analysis. The lead information, along with the sentiment score, is then added to a Google Sheets spreadsheet.
WhatConverts + Google Vertex AI + Slack: When WhatConverts captures a new lead, use Vertex AI to analyze the lead's details. Then send a summary of that analysis to a designated Slack channel for quick review.
Google Vertex AI and WhatConverts 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 WhatConverts
Capture and analyze marketing leads in WhatConverts, then pipe data to Latenode to automate follow-ups. Qualify leads based on source & behavior using Latenode's no-code tools, triggering custom CRM updates or personalized email sequences. Scale lead management without complex coding.
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FAQ Google Vertex AI and WhatConverts
How can I connect my Google Vertex AI account to WhatConverts using Latenode?
To connect your Google Vertex AI account to WhatConverts 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 WhatConverts accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze lead quality using AI summaries?
Yes, use Google Vertex AI to summarize WhatConverts data. Latenode’s visual editor makes it easy. Gain insights and qualify leads faster by analyzing call transcripts and form submissions.
What types of tasks can I perform by integrating Google Vertex AI with WhatConverts?
Integrating Google Vertex AI with WhatConverts allows you to perform various tasks, including:
- Enrich WhatConverts lead data with AI-powered sentiment analysis.
- Automatically tag leads based on Google Vertex AI's topic extraction.
- Generate personalized follow-up emails using Google Vertex AI, triggered by WhatConverts.
- Use AI to identify high-value keywords from call transcripts in WhatConverts.
- Route leads to specific teams based on AI analysis of conversion data.
Can I use custom JavaScript functions with Vertex AI on Latenode?
Yes, Latenode supports custom JavaScript. Enhance your Google Vertex AI workflows by manipulating data, integrating APIs, and adding custom logic.
Are there any limitations to the Google Vertex AI and WhatConverts integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large volumes of data processed by Google Vertex AI may incur higher processing costs.
- Real-time analysis depends on the speed of the Google Vertex AI API.
- Custom models in Google Vertex AI require additional training and configuration.