Google AI and CloudTalk Integration

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Automatically analyze CloudTalk call transcripts using Google AI to extract key insights and sentiment. Build advanced logic with JavaScript in Latenode, scaling affordably as call volumes grow with our pay-by-execution pricing.

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Google AI

CloudTalk

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google AI and CloudTalk

Create a New Scenario to Connect Google 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 AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google AI or CloudTalk will be your first step. To do this, click "Choose an app," find Google AI or CloudTalk, and select the appropriate trigger to start the scenario.

Add the Google AI Node

Select the Google AI node from the app selection panel on the right.

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Configure the Google AI

Click on the Google AI node to configure it. You can modify the Google AI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the CloudTalk Node

Next, click the plus (+) icon on the Google 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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Sign In

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Configure the Google 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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Run node once

Set Up the Google 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 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 AI and CloudTalk integration works as expected. Depending on your setup, data should flow between Google 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 AI and CloudTalk

CloudTalk + Google AI + Salesforce: When a new call is recorded in CloudTalk, the transcript is sent to Google AI to summarize the call and determine sentiment. The summary and sentiment are then logged as a new record in Salesforce.

CloudTalk + Google AI + Slack: When a new call is made in CloudTalk, the transcript is analyzed by Google AI for urgent keywords. If found, a message is sent to a designated Slack channel to alert a supervisor.

Google AI and CloudTalk integration alternatives

About Google AI

Use Google AI in Latenode to add smarts to your workflows. Process text, translate languages, or analyze images automatically. Unlike direct API calls, Latenode lets you combine AI with other apps, add logic, and scale without code. Automate content moderation, sentiment analysis, and more.

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 AI and CloudTalk

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

To connect your Google AI account to CloudTalk on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google AI and click on "Connect".
  • Authenticate your Google AI and CloudTalk accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I analyze call sentiment using Google AI and CloudTalk?

Yes, you can! Latenode lets you automatically analyze CloudTalk call transcripts with Google AI for sentiment. This helps quickly identify customer satisfaction trends and improve agent performance.

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

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

  • Automatically summarize call transcripts from CloudTalk using Google AI.
  • Route calls based on real-time sentiment analysis via Google AI.
  • Create personalized follow-up emails using Google AI based on call content.
  • Identify trending topics in customer conversations using AI insights.
  • Enrich contact profiles in CloudTalk with data derived from Google AI.

Can I use custom prompts with Google AI on Latenode?

Yes! Latenode supports custom prompts for Google AI. Tailor AI responses to specific needs, enhancing accuracy and relevance across all CloudTalk interactions.

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

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

  • Large volumes of call data may impact processing speed.
  • Accuracy of AI depends on the quality of call transcripts.
  • Custom code knowledge may be needed for advanced workflows.

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