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

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Authenticate TimeCamp
Now, click the TimeCamp node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your TimeCamp settings. Authentication allows you to use TimeCamp through Latenode.
Configure the Google Vertex AI and TimeCamp 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 TimeCamp 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 Vertex AI, TimeCamp, 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 TimeCamp integration works as expected. Depending on your setup, data should flow between Google Vertex AI and TimeCamp (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 TimeCamp
TimeCamp + Google Vertex AI + Google Sheets: When a new time entry is logged in TimeCamp, the description is sent to Google Vertex AI for sentiment analysis. The sentiment score is then logged into a Google Sheet along with the original time entry data.
TimeCamp + Google Vertex AI + Slack: At the end of each week (this part requires an external scheduler), TimeCamp's time entries for a specific project are summarized using Google Vertex AI. The summarized performance overview is then posted in a dedicated Slack channel.
Google Vertex AI and TimeCamp 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 TimeCamp
Track time in TimeCamp, then use Latenode to automate payroll, project costing, or client billing. Connect time data to accounting software or project management tools. Latenode's visual editor makes it easy to build custom workflows, avoiding manual data entry and improving reporting accuracy.
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See how Latenode works
FAQ Google Vertex AI and TimeCamp
How can I connect my Google Vertex AI account to TimeCamp using Latenode?
To connect your Google Vertex AI account to TimeCamp 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 TimeCamp accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate project time tracking using AI insights?
Yes! Latenode lets you use AI-powered insights from Google Vertex AI to automatically update TimeCamp, streamlining project management & boosting team productivity using AI and no-code.
What types of tasks can I perform by integrating Google Vertex AI with TimeCamp?
Integrating Google Vertex AI with TimeCamp allows you to perform various tasks, including:
- Automatically log time against tasks based on AI analysis of project communication.
- Use AI to categorize time entries based on project activity keywords.
- Generate project reports in TimeCamp enhanced with AI-driven insights.
- Predict project completion times using AI and track progress in TimeCamp.
- Analyze time allocation in TimeCamp to optimize resource management using AI.
What kind of Google Vertex AI models can I use in Latenode?
Latenode supports Vertex AI's PaLM, Gemini, Imagen, and other models, empowering tailored AI solutions for your automation workflows.
Are there any limitations to the Google Vertex AI and TimeCamp integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex AI models may consume significant Latenode execution units.
- TimeCamp's API rate limits can affect high-volume data processing.
- Custom AI model training requires a separate Google Vertex AI setup.