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

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Authenticate Avaza
Now, click the Avaza node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Avaza settings. Authentication allows you to use Avaza through Latenode.
Configure the Google Vertex AI and Avaza 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 Avaza 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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AI Anthropic Claude 3
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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Vertex AI, Avaza, 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 Avaza integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Avaza (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 Avaza
Avaza + Google Vertex AI + Slack: When a new event occurs in Avaza, such as a project update, the details are sent to Google Vertex AI to analyze project progress. A summary report is then sent to a designated Slack channel.
Avaza + Google Vertex AI + Google Sheets: Track project costs in Avaza. If costs are updated, send the updated data to Google Vertex AI to predict budget overruns. Log these predictions, along with the Avaza data, into Google Sheets for tracking and analysis.
Google Vertex AI and Avaza 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 Avaza
Automate project management with Avaza in Latenode. Create flows that sync tasks, track time, and manage expenses automatically. Use Latenode's visual editor to tailor Avaza workflows and connect them to other apps. Streamline reporting and billing cycles with no-code logic and custom scripts for efficient project oversight.
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FAQ Google Vertex AI and Avaza
How can I connect my Google Vertex AI account to Avaza using Latenode?
To connect your Google Vertex AI account to Avaza 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 Avaza accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically update Avaza tasks based on AI insights?
Yes, you can! Latenode allows AI-powered task updates, keeping projects on track. Use Google Vertex AI to analyze project data, then automatically adjust Avaza tasks for optimal resource allocation.
What types of tasks can I perform by integrating Google Vertex AI with Avaza?
Integrating Google Vertex AI with Avaza allows you to perform various tasks, including:
- Automatically create Avaza tasks from AI-analyzed customer feedback.
- Prioritize projects based on sentiment analysis of client communications.
- Generate project summaries for Avaza using AI-powered content creation.
- Identify potential project risks based on AI-driven predictive analysis.
- Update task assignments in Avaza using AI skill-matching suggestions.
How scalable is Google Vertex AI automation?
Latenode's architecture allows Google Vertex AI automation to scale with your needs. Handle increasing data volumes and complex workflows without performance bottlenecks.
Are there any limitations to the Google Vertex AI and Avaza integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex AI models in Google Vertex AI may require significant processing time.
- Data transfer limits from Avaza are subject to your Avaza subscription plan.
- Custom AI training requires a strong understanding of machine learning.