How to connect Google Vertex AI and ServiceM8
Create a New Scenario to Connect Google Vertex AI and ServiceM8
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 ServiceM8 will be your first step. To do this, click "Choose an app," find Google Vertex AI or ServiceM8, 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 ServiceM8 Node
Next, click the plus (+) icon on the Google Vertex AI node, select ServiceM8 from the list of available apps, and choose the action you need from the list of nodes within ServiceM8.

Google Vertex AI
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ServiceM8

Authenticate ServiceM8
Now, click the ServiceM8 node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your ServiceM8 settings. Authentication allows you to use ServiceM8 through Latenode.
Configure the Google Vertex AI and ServiceM8 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 ServiceM8 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
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AI Anthropic Claude 3
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ServiceM8
Trigger on Webhook
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Google Vertex AI
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring Google Vertex AI, ServiceM8, 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 ServiceM8 integration works as expected. Depending on your setup, data should flow between Google Vertex AI and ServiceM8 (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 ServiceM8
ServiceM8 + Google Vertex AI + Slack: When a job is completed in ServiceM8, the details are sent to Google Vertex AI to analyze the customer feedback. If negative feedback is detected, a message is sent to a dedicated Slack channel alerting the team.
ServiceM8 + Google Vertex AI + Google Sheets: When a job is completed in ServiceM8, the job report details are sent to Google Vertex AI for summarization. The key findings from the summary are then stored in a Google Sheet for further analysis and tracking.
Google Vertex AI and ServiceM8 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 ServiceM8
Sync ServiceM8 field service data with other apps inside Latenode to automate scheduling, invoicing, and client communication. Use Latenode's visual editor to build custom workflows triggered by ServiceM8 events, avoiding manual data entry. Connect accounting, CRM, and marketing tools, extending ServiceM8's capabilities without complex coding.
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FAQ Google Vertex AI and ServiceM8
How can I connect my Google Vertex AI account to ServiceM8 using Latenode?
To connect your Google Vertex AI account to ServiceM8 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 ServiceM8 accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze ServiceM8 feedback using Vertex AI?
Yes, you can! Latenode lets you send ServiceM8 feedback to Vertex AI for sentiment analysis, automatically improving service and identifying crucial areas.
What types of tasks can I perform by integrating Google Vertex AI with ServiceM8?
Integrating Google Vertex AI with ServiceM8 allows you to perform various tasks, including:
- Automatically categorize support requests using Vertex AI's natural language processing.
- Summarize ServiceM8 job details using Vertex AI to generate concise reports.
- Predict potential equipment failures based on ServiceM8 data using Vertex AI models.
- Generate personalized upsell recommendations in ServiceM8 using Vertex AI insights.
- Automatically draft service responses using Vertex AI based on ServiceM8 job information.
How does Latenode handle Vertex AI authentication for ServiceM8?
Latenode uses secure OAuth, managing authentication behind the scenes, letting you focus on building powerful integrations easily.
Are there any limitations to the Google Vertex AI and ServiceM8 integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex Vertex AI model deployments might require custom JavaScript nodes.
- Very high-volume ServiceM8 data processing may require optimized workflow design.
- Access to specific Vertex AI features depends on your Google Cloud subscription level.