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

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Authenticate Inoreader
Now, click the Inoreader node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Inoreader settings. Authentication allows you to use Inoreader through Latenode.
Configure the Google Vertex AI and Inoreader 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 Inoreader 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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Inoreader
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Vertex AI, Inoreader, 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 Inoreader integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Inoreader (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 Inoreader
Inoreader + Google Vertex AI + Slack: This automation monitors a specific Inoreader folder for new articles. When a new article appears, its content is sent to Google Vertex AI to generate a summary. The generated summary is then posted to a designated Slack channel.
Inoreader + Google Vertex AI + Google Sheets: This flow monitors Inoreader for new articles based on a subscription. When a new article is found, its content is analyzed using Google Vertex AI to extract key data. This data is then added as a new row to a Google Sheet for tracking and analysis.
Google Vertex AI and Inoreader 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 Inoreader
Aggregate and filter news feeds in Inoreader, then use Latenode to automate actions based on specific articles. Trigger alerts, update databases, or post to social media directly from your curated content. Use Latenode's visual editor and JavaScript node to refine filtering and formatting rules far beyond Inoreader's native options.
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See how Latenode works
FAQ Google Vertex AI and Inoreader
How can I connect my Google Vertex AI account to Inoreader using Latenode?
To connect your Google Vertex AI account to Inoreader 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 Inoreader accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze news feeds with AI using Google Vertex AI and Inoreader?
Yes, Latenode enables AI-driven analysis. Automate content summarization and sentiment analysis to extract insights, saving time with powerful no-code AI workflows.
What types of tasks can I perform by integrating Google Vertex AI with Inoreader?
Integrating Google Vertex AI with Inoreader allows you to perform various tasks, including:
- Automatically categorize Inoreader articles using Vertex AI's natural language processing.
- Summarize lengthy news articles from Inoreader using Vertex AI's text generation.
- Detect trends in Inoreader feeds by analyzing article sentiment with Vertex AI.
- Forward targeted Inoreader articles to specific teams based on Vertex AI analysis.
- Create custom alerts based on combined Inoreader content and Vertex AI insights.
Can I use custom JavaScript code to transform data between the apps?
Yes, Latenode allows you to use JavaScript code blocks to transform data, making the integration more flexible and adaptable to your specific needs.
Are there any limitations to the Google Vertex AI and Inoreader integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex AI models may require substantial processing time, affecting workflow speed.
- The number of API calls to both Google Vertex AI and Inoreader are subject to rate limits.
- Data transformation limitations depend on the capabilities of the chosen AI models.