How to connect AITable and Google Vertex AI
Create a New Scenario to Connect AITable and Google Vertex AI
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 AITable, triggered by another scenario, or executed manually (for testing purposes). In most cases, AITable or Google Vertex AI will be your first step. To do this, click "Choose an app," find AITable or Google Vertex AI, and select the appropriate trigger to start the scenario.

Add the AITable Node
Select the AITable node from the app selection panel on the right.

AITable
Add the Google Vertex AI Node
Next, click the plus (+) icon on the AITable node, select Google Vertex AI from the list of available apps, and choose the action you need from the list of nodes within Google Vertex AI.

AITable
âš™
Google Vertex AI
Authenticate Google Vertex AI
Now, click the Google Vertex AI node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Vertex AI settings. Authentication allows you to use Google Vertex AI through Latenode.
Configure the AITable and Google Vertex AI 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 AITable and Google Vertex AI 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
âš™
AI Anthropic Claude 3
âš™
Google Vertex AI
Trigger on Webhook
âš™
AITable
âš™
âš™
Iterator
âš™
Webhook response
Save and Activate the Scenario
After configuring AITable, Google Vertex AI, 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 AITable and Google Vertex AI integration works as expected. Depending on your setup, data should flow between AITable and Google Vertex AI (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect AITable and Google Vertex AI
AITable + Google Vertex AI + Slack: When a new record is created in AITable, analyze the data using Google Vertex AI's Gemini model to summarize key insights, and then post an update with the summary to a designated Slack channel.
Google Vertex AI + AITable + Google Sheets: Use Google Vertex AI's Gemini model to generate content. Store the generated content as a new record in AITable, and then export that record data to a Google Sheet for reporting purposes.
AITable and Google Vertex AI integration alternatives
About AITable
Manage project data in AITable and sync it with Latenode for powerful automation. Update databases, trigger notifications, or generate reports based on AITable changes. Latenode adds logic and integrations, creating workflows that AITable alone can't provide. Scale custom apps with ease, paying only for execution time.
Related categories
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.
Related categories
See how Latenode works
FAQ AITable and Google Vertex AI
How can I connect my AITable account to Google Vertex AI using Latenode?
To connect your AITable account to Google Vertex AI on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select AITable and click on "Connect".
- Authenticate your AITable and Google Vertex AI accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically analyze AITable data with Vertex AI?
Yes, you can! Latenode enables seamless data transfer and AI analysis, enriching AITable records with insights, powered by Vertex AI. Automate your data workflows effortlessly.
What types of tasks can I perform by integrating AITable with Google Vertex AI?
Integrating AITable with Google Vertex AI allows you to perform various tasks, including:
- Automatically classify customer feedback stored in AITable using Vertex AI.
- Generate product descriptions for AITable listings with Vertex AI's language models.
- Perform sentiment analysis on survey responses recorded in AITable.
- Extract key information from documents and store it in AITable using Vertex AI.
- Predict future sales trends based on AITable data with Vertex AI's machine learning.
How do I handle large AITable datasets when using Google Vertex AI?
Latenode supports batch processing and data streaming, allowing you to efficiently manage large AITable datasets for Vertex AI analysis without performance bottlenecks.
Are there any limitations to the AITable and Google Vertex AI integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits on the AITable API and Google Vertex AI API may affect performance.
- Complex data transformations may require custom JavaScript code.
- Real-time data synchronization is subject to network latency.