Google Vertex AI and CloudTalk Integration

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Use Google Vertex AI to analyze CloudTalk call transcripts for sentiment and intent. Route calls, flag issues, and summarize interactions automatically, all in Latenode’s visual editor with affordable execution-based pricing. Build advanced automations with low-code and JavaScript support.

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Google Vertex AI

CloudTalk

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Vertex AI and CloudTalk

Create a New Scenario to Connect Google Vertex AI and CloudTalk

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 CloudTalk will be your first step. To do this, click "Choose an app," find Google Vertex AI or CloudTalk, 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.

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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.

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Add the CloudTalk Node

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

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Authenticate CloudTalk

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

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Configure the Google Vertex AI and CloudTalk Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the Google Vertex AI and CloudTalk 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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Save and Activate the Scenario

After configuring Google Vertex AI, CloudTalk, 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 CloudTalk integration works as expected. Depending on your setup, data should flow between Google Vertex AI and CloudTalk (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 CloudTalk

CloudTalk + Google Vertex AI + Salesforce: When a new call is received in CloudTalk, the audio file is analyzed by Google Vertex AI to identify key topics and sentiment. This analysis is then used to update the corresponding lead's record in Salesforce, adjusting their lead score based on the call's insights.

CloudTalk + Google Vertex AI + Zendesk: When a new call ends in CloudTalk, the audio of call is analyzed by Google Vertex AI to generate a summary of the call's content. This summary is then used to automatically create a new ticket in Zendesk, pre-populated with the call summary and other relevant details, such as contact information.

Google Vertex AI and CloudTalk 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.

About CloudTalk

Automate CloudTalk call and SMS data within Latenode. Trigger workflows on new calls, messages, or agent status changes. Update CRMs, send alerts, or generate reports automatically. Use Latenode's visual editor and data transformation tools to customize call center automations without complex coding, and scale your workflows efficiently.

See how Latenode works

FAQ Google Vertex AI and CloudTalk

How can I connect my Google Vertex AI account to CloudTalk using Latenode?

To connect your Google Vertex AI account to CloudTalk 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 CloudTalk accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I analyze call transcripts with AI and update contact details?

Yes, you can! Latenode lets you use Google Vertex AI to analyze CloudTalk call transcripts and automatically update contact details, saving time and improving data accuracy.

What types of tasks can I perform by integrating Google Vertex AI with CloudTalk?

Integrating Google Vertex AI with CloudTalk allows you to perform various tasks, including:

  • Automatically summarize call transcripts using AI.
  • Analyze customer sentiment from call recordings.
  • Categorize calls based on the content discussed.
  • Update customer information based on call details.
  • Trigger personalized follow-up actions after calls.

How do I use custom AI models from Google Vertex AI inside Latenode?

Latenode allows you to integrate custom Google Vertex AI models using API calls, giving you advanced control and flexibility.

Are there any limitations to the Google Vertex AI and CloudTalk integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Complex workflows may require JavaScript knowledge.
  • Google Vertex AI usage is subject to Google’s pricing.
  • Real-time transcript analysis has inherent latency.

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