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

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Google Cloud Text-To-Speech

Authenticate Google Cloud Text-To-Speech
Now, click the Google Cloud Text-To-Speech node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud Text-To-Speech settings. Authentication allows you to use Google Cloud Text-To-Speech through Latenode.
Configure the Google Vertex AI and Google Cloud Text-To-Speech 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 Google Cloud Text-To-Speech 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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Google Cloud Text-To-Speech
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, Google Cloud Text-To-Speech, 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 Google Cloud Text-To-Speech integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Google Cloud Text-To-Speech (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 Google Cloud Text-To-Speech
Slack + Google Vertex AI + Google Cloud Text-To-Speech: When a new message is posted to a Slack channel, the message content is analyzed using Google Vertex AI. If the analysis identifies customer feedback, a summary of the feedback is created using Google Cloud Text-To-Speech and sent back to the Slack channel.
HubSpot + Google Vertex AI + Google Cloud Text-To-Speech: When a new blog post is created in HubSpot, Google Vertex AI generates personalized audio content based on the blog post content. Then Google Cloud Text-To-Speech converts this content into speech and creates audio. Finally the contact in Hubspot will be updated.
Google Vertex AI and Google Cloud Text-To-Speech 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 Google Cloud Text-To-Speech
Use Google Cloud Text-To-Speech in Latenode to automate voice notifications, generate audio content from text, and create dynamic IVR systems. Integrate it into any workflow with a drag-and-drop interface. No code is required, and it's fully customizable with JavaScript for complex text manipulations. Automate voice tasks efficiently without vendor lock-in.
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FAQ Google Vertex AI and Google Cloud Text-To-Speech
How can I connect my Google Vertex AI account to Google Cloud Text-To-Speech using Latenode?
To connect your Google Vertex AI account to Google Cloud Text-To-Speech 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 Google Cloud Text-To-Speech accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate personalized voice message generation?
Yes! Latenode enables you to automate voice messages using Vertex AI for personalized content and Text-To-Speech for natural voices. Boost engagement with unique, automated communications.
What types of tasks can I perform by integrating Google Vertex AI with Google Cloud Text-To-Speech?
Integrating Google Vertex AI with Google Cloud Text-To-Speech allows you to perform various tasks, including:
- Automatically create audio summaries of long-form text generated by Vertex AI.
- Build interactive voice responses powered by AI-driven content generation.
- Generate personalized audio ads based on user profiles from Vertex AI insights.
- Automate voiceovers for videos using AI-generated scripts.
- Convert AI-created chatbots conversations into natural-sounding audio.
How do I handle API authentication for Google Vertex AI in Latenode?
Latenode simplifies API authentication through secure credential storage and a user-friendly interface, ensuring a seamless workflow setup.
Are there any limitations to the Google Vertex AI and Google Cloud Text-To-Speech integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex workflows with high data volumes may require optimized node configurations.
- Custom voice models from Google Cloud Text-To-Speech need to be properly configured.
- The length of text processed by Vertex AI is subject to the platform's constraints.