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integrationGoogle Gemini Chat Model node
integrationServiceNow node

Google Gemini Chat Model and ServiceNow integration

Save yourself the work of writing custom integrations for Google Gemini Chat Model and ServiceNow and use n8n instead. Build adaptable and scalable AI, Langchain, Productivity, and Communication workflows that work with your technology stack. All within a building experience you will love.

How to connect Google Gemini Chat Model and ServiceNow

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Google Gemini Chat Model and ServiceNow integration: Create a new workflow and add the first step

Step 2: Add and configure Google Gemini Chat Model and ServiceNow nodes

You can find Google Gemini Chat Model and ServiceNow in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Google Gemini Chat Model and ServiceNow nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Google Gemini Chat Model and ServiceNow integration: Add and configure Google Gemini Chat Model and ServiceNow nodes

Step 3: Connect Google Gemini Chat Model and ServiceNow

A connection establishes a link between Google Gemini Chat Model and ServiceNow (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Google Gemini Chat Model and ServiceNow integration: Connect Google Gemini Chat Model and ServiceNow

Step 4: Customize and extend your Google Gemini Chat Model and ServiceNow integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Google Gemini Chat Model and ServiceNow with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Google Gemini Chat Model and ServiceNow integration: Customize and extend your Google Gemini Chat Model and ServiceNow integration

Step 5: Test and activate your Google Gemini Chat Model and ServiceNow workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Google Gemini Chat Model to ServiceNow or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Google Gemini Chat Model and ServiceNow integration: Test and activate your Google Gemini Chat Model and ServiceNow workflow

Automate ITSM ticket classification and resolution using Gemini, Qdrant and ServiceNow

Who’s it for
This template is ideal for IT support teams, internal helpdesk automation engineers, and developers building intelligent ticketing systems. It helps streamline ITSM workflows by automatically classifying user queries, retrieving relevant knowledge base entries, and triggering incident creation in ServiceNow.

How it works / What it does
This workflow uses Google Gemini and Qdrant to power an intelligent ITSM assistant. When a user submits a query via chat:

The Text Classifier categorizes the input as an Incident, Request, or Other.
Based on the category:

Incidents are automatically logged in ServiceNow.
Requests trigger an HTTP call (e.g., for provisioning or access).
Other queries are routed to an AI Agent that searches the FAQBase in Qdrant and responds contextually.

The Gemini LLM enriches responses and summaries.
The Qdrant Vector Store retrieves semantically similar answers from a pre-embedded FAQ knowledge base.
The Summarization Chain condenses incident details for better tracking.

Sticky notes are used throughout the workflow to document each node’s purpose and improve maintainability.

How to set up

Connect your Google Gemini API, Qdrant, and ServiceNow credentials.
Populate the FAQBase collection in Qdrant with your ITSM knowledge base.
Deploy the webhook to receive chat inputs.
Test the flow using the Manual Trigger node.
Customize the classifier categories and Gemini prompts as needed.

Requirements

Google Gemini API access
Qdrant vector database with embedded FAQ data
ServiceNow account with API access
n8n instance with LangChain nodes installed

How to customize the workflow

Modify the Text Classifier categories to suit your organization’s ticket types.
Add more FAQ entries to Qdrant for broader coverage.
Replace the HTTP Request node with integrations relevant to your ITSM tools.
Adjust the Gemini prompts to reflect your tone and support style.
Extend the workflow with Slack, Teams, or email notifications for ticket updates.

Nodes used in this workflow

Popular Google Gemini Chat Model and ServiceNow workflows

+5

Automate ITSM ticket classification and resolution using Gemini, Qdrant and ServiceNow

Who’s it for This template is ideal for IT support teams, internal helpdesk automation engineers, and developers building intelligent ticketing systems. It helps streamline ITSM workflows by automatically classifying user queries, retrieving relevant knowledge base entries, and triggering incident creation in ServiceNow. How it works / What it does This workflow uses Google Gemini and Qdrant to power an intelligent ITSM assistant. When a user submits a query via chat: The Text Classifier categorizes the input as an Incident, Request, or Other. Based on the category: Incidents are automatically logged in ServiceNow. Requests trigger an HTTP call (e.g., for provisioning or access). Other queries are routed to an AI Agent that searches the FAQBase in Qdrant and responds contextually. The Gemini LLM enriches responses and summaries. The Qdrant Vector Store retrieves semantically similar answers from a pre-embedded FAQ knowledge base. The Summarization Chain condenses incident details for better tracking. Sticky notes are used throughout the workflow to document each node’s purpose and improve maintainability. How to set up Connect your Google Gemini API, Qdrant, and ServiceNow credentials. Populate the FAQBase collection in Qdrant with your ITSM knowledge base. Deploy the webhook to receive chat inputs. Test the flow using the Manual Trigger node. Customize the classifier categories and Gemini prompts as needed. Requirements Google Gemini API access Qdrant vector database with embedded FAQ data ServiceNow account with API access n8n instance with LangChain nodes installed How to customize the workflow Modify the Text Classifier categories to suit your organization’s ticket types. Add more FAQ entries to Qdrant for broader coverage. Replace the HTTP Request node with integrations relevant to your ITSM tools. Adjust the Gemini prompts to reflect your tone and support style. Extend the workflow with Slack, Teams, or email notifications for ticket updates.

Build your own Google Gemini Chat Model and ServiceNow integration

Create custom Google Gemini Chat Model and ServiceNow workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

ServiceNow supported actions

Upload
Upload an attachment to a specific table record
Delete
Delete an attachment
Get
Get an attachment
Get Many
Get many attachments on a table
Get Many
Get Many
Get Many
Get Many
Create
Delete
Get
Get Many
Update
Create
Delete
Get
Get Many
Update
Create
Delete
Get
Get Many
Update
Get Many
Get Many

FAQs

  • Can Google Gemini Chat Model connect with ServiceNow?

  • Can I use Google Gemini Chat Model’s API with n8n?

  • Can I use ServiceNow’s API with n8n?

  • Is n8n secure for integrating Google Gemini Chat Model and ServiceNow?

  • How to get started with Google Gemini Chat Model and ServiceNow integration in n8n.io?

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