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

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Amazon SES

Authenticate Amazon SES
Now, click the Amazon SES node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Amazon SES settings. Authentication allows you to use Amazon SES through Latenode.
Configure the Google Vertex AI and Amazon SES 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 Amazon SES 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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Amazon SES
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, Amazon SES, 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 Amazon SES integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Amazon SES (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 Amazon SES
Amazon SES + Google Vertex AI + Google Sheets: Upon receiving a new verified identity in Amazon SES, customer feedback is analyzed using Google Vertex AI to extract sentiment. The analysis results, along with the original feedback, are then logged in a Google Sheets spreadsheet for future review and insights.
Amazon SES + Google Vertex AI + Slack: When a new verified identity is added to Amazon SES, the text is analyzed by Google Vertex AI to detect urgent issues. If urgent issues are detected, a notification with the analyzed text is sent to a designated Slack channel to alert support teams.
Google Vertex AI and Amazon SES 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 Amazon SES
Automate email sending with Amazon SES in Latenode. Send transactional emails, notifications, and marketing campaigns within your automated workflows. Use Latenode's visual editor to connect SES to other apps, add conditional logic, and handle bounces – simplifying email management and scaling your communication flows without coding.
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FAQ Google Vertex AI and Amazon SES
How can I connect my Google Vertex AI account to Amazon SES using Latenode?
To connect your Google Vertex AI account to Amazon SES 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 Amazon SES accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I personalize marketing emails with AI-generated content?
Yes, you can! Latenode allows you to generate personalized content using Google Vertex AI and send it via Amazon SES, improving engagement with tailored messaging at scale.
What types of tasks can I perform by integrating Google Vertex AI with Amazon SES?
Integrating Google Vertex AI with Amazon SES allows you to perform various tasks, including:
- Automatically generate email subject lines using AI.
- Analyze customer data to personalize email content.
- Route customer inquiries to the best AI model for response.
- Create dynamic email campaigns based on AI insights.
- Monitor email sentiment and adjust messaging accordingly.
Can I use Javascript code to enhance my Google Vertex AI automations?
Yes! Latenode allows you to use Javascript for advanced Google Vertex AI workflows, adding custom logic and data transformations beyond the visual editor.
Are there any limitations to the Google Vertex AI and Amazon SES integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large volumes of AI requests may incur Google Vertex AI costs.
- Amazon SES has sending limits based on your account reputation.
- Complex AI models may increase workflow execution time.