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

Google Vertex AI
⚙
JobNimbus
Authenticate JobNimbus
Now, click the JobNimbus node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your JobNimbus settings. Authentication allows you to use JobNimbus through Latenode.
Configure the Google Vertex AI and JobNimbus 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 JobNimbus 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
⚙
JobNimbus
Trigger on Webhook
⚙
Google Vertex AI
⚙
⚙
Iterator
⚙
Webhook response
Save and Activate the Scenario
After configuring Google Vertex AI, JobNimbus, 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 JobNimbus integration works as expected. Depending on your setup, data should flow between Google Vertex AI and JobNimbus (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 JobNimbus
JobNimbus + Google Vertex AI + Slack: When new feedback is captured in JobNimbus, the AI analyzes the sentiment and posts the result in a designated Slack channel for team review.
JobNimbus + Google Vertex AI + Google Sheets: As job notes are updated in JobNimbus, AI categorizes them and appends these categorizations to a Google Sheet for trend tracking and analysis.
Google Vertex AI and JobNimbus 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 JobNimbus
Automate Instagram Business tasks within Latenode. Schedule posts, extract comments, and analyze metrics without manual effort. Integrate Instagram data with CRMs or spreadsheets. Latenode offers flexible logic and affordable scaling, so you can manage social media workflows alongside other business processes using AI tools or custom scripts.
Similar apps
Related categories
See how Latenode works
FAQ Google Vertex AI and JobNimbus
How can I connect my Google Vertex AI account to JobNimbus using Latenode?
To connect your Google Vertex AI account to JobNimbus 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 JobNimbus accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze customer feedback from JobNimbus using Vertex AI?
Yes, you can! With Latenode, easily send JobNimbus feedback to Vertex AI for sentiment analysis. This proactive approach identifies negative trends and improves customer satisfaction.
What types of tasks can I perform by integrating Google Vertex AI with JobNimbus?
Integrating Google Vertex AI with JobNimbus allows you to perform various tasks, including:
- Automatically generate personalized follow-up emails after service completion.
- Use AI to categorize and prioritize customer support requests efficiently.
- Extract key insights from customer reviews for improved service offerings.
- Predict potential project delays based on historical JobNimbus data.
- Create automated reports summarizing project performance using AI analysis.
How do I pass data between Google Vertex AI and JobNimbus in Latenode?
Latenode's visual editor lets you easily map data fields between Google Vertex AI and JobNimbus, ensuring seamless information flow.
Are there any limitations to the Google Vertex AI and JobNimbus integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers may incur processing time depending on Vertex AI's limits.
- Custom JavaScript coding might be required for extremely complex data transformations.
- Certain highly specialized Vertex AI models may need separate configuration.