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

Google Vertex AI
⚙

Freshdesk

Authenticate Freshdesk
Now, click the Freshdesk node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Freshdesk settings. Authentication allows you to use Freshdesk through Latenode.
Configure the Google Vertex AI and Freshdesk 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 Freshdesk 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
⚙
AI Anthropic Claude 3
⚙

Freshdesk
Trigger on Webhook
⚙
Google Vertex AI
⚙
⚙
Iterator
⚙
Webhook response

Save and Activate the Scenario
After configuring Google Vertex AI, Freshdesk, 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 Freshdesk integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Freshdesk (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 Freshdesk
Freshdesk + Google Vertex AI + Slack: When a new ticket is created in Freshdesk, its content is analyzed by Vertex AI to determine the sentiment. If the sentiment is negative, a message is sent to a designated Slack channel to alert the support team.
Freshdesk + Google Vertex AI + Google Sheets: When a new ticket is created in Freshdesk, Vertex AI generates a summary of the ticket. The summary, along with the ticket ID, is then added as a new row in a Google Sheets spreadsheet for tracking and analysis.
Google Vertex AI and Freshdesk 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.
Similar apps
Related categories

About Freshdesk
Sync Freshdesk tickets with other apps in Latenode to automate support workflows. Update databases, trigger alerts, or generate reports based on ticket status, all without code. Connect Freshdesk to your CRM or marketing tools to close the loop on customer issues. Less manual work, more automation.
Related categories
See how Latenode works
FAQ Google Vertex AI and Freshdesk
How can I connect my Google Vertex AI account to Freshdesk using Latenode?
To connect your Google Vertex AI account to Freshdesk 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 Freshdesk accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically analyze customer support tickets with AI?
Yes, you can! Latenode’s visual editor makes it easy to send Freshdesk tickets to Google Vertex AI for sentiment analysis, routing urgent issues faster and improving response times.
What types of tasks can I perform by integrating Google Vertex AI with Freshdesk?
Integrating Google Vertex AI with Freshdesk allows you to perform various tasks, including:
- Automatically classify support tickets using AI models.
- Summarize lengthy customer inquiries using Vertex AI.
- Translate customer support requests into different languages.
- Detect the sentiment of customer feedback and prioritize responses.
- Suggest relevant knowledge base articles based on ticket content.
What Google Vertex AI models work best for Freshdesk automation?
Language models like Text Bison are ideal for sentiment analysis, summarization, and classification in your Freshdesk workflows, all in Latenode.
Are there any limitations to the Google Vertex AI and Freshdesk integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- The number of requests to Google Vertex AI is limited by your Google Cloud project's quota.
- Large data transfers between apps may impact workflow execution speed.
- Custom model training requires a separate Google Vertex AI setup process.