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

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Authenticate LinkedIn Data Scraper
Now, click the LinkedIn Data Scraper node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your LinkedIn Data Scraper settings. Authentication allows you to use LinkedIn Data Scraper through Latenode.
Configure the Google Vertex AI and LinkedIn Data Scraper 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 LinkedIn Data Scraper 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Vertex AI, LinkedIn Data Scraper, 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 LinkedIn Data Scraper integration works as expected. Depending on your setup, data should flow between Google Vertex AI and LinkedIn Data Scraper (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 LinkedIn Data Scraper
LinkedIn Data Scraper + Google Vertex AI + Google Sheets: Scrape LinkedIn job postings for specific skills using the LinkedIn Data Scraper. Then, analyze the scraped job description text with Google Vertex AI (Gemini) to extract key skills and technologies. Finally, save the extracted skills data to a Google Sheet.
LinkedIn Data Scraper + Google Vertex AI + Slack: Scrape LinkedIn for leads using LinkedIn Data Scraper. Use Google Vertex AI (Gemini) to generate personalized message drafts based on the lead's profile data. Send a notification to Slack with the lead information and suggested message.
Google Vertex AI and LinkedIn Data Scraper 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 LinkedIn Data Scraper
Need LinkedIn data for leads or market insights? Automate scraping profiles and company info inside Latenode workflows. Extract data, enrich it with AI, then push it to your CRM or database. Latenode's visual editor and affordable pricing make data-driven outreach scalable and cost-effective.
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FAQ Google Vertex AI and LinkedIn Data Scraper
How can I connect my Google Vertex AI account to LinkedIn Data Scraper using Latenode?
To connect your Google Vertex AI account to LinkedIn Data Scraper 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 LinkedIn Data Scraper accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze scraped LinkedIn profiles with AI?
Yes, you can! Latenode enables seamless data transfer to Google Vertex AI for sentiment analysis, skills extraction, and more, boosting lead qualification with AI insights.
What types of tasks can I perform by integrating Google Vertex AI with LinkedIn Data Scraper?
Integrating Google Vertex AI with LinkedIn Data Scraper allows you to perform various tasks, including:
- Enriching scraped lead data with AI-powered insights.
- Automating personalized outreach based on profile analysis.
- Identifying potential candidates using AI skill matching.
- Monitoring industry trends via AI-driven content analysis.
- Generating summaries of LinkedIn profiles with Vertex AI.
What Google Vertex AI models can I use in Latenode workflows?
Latenode supports any Vertex AI model, empowering custom NLP and data analysis within your LinkedIn Data Scraper automations.
Are there any limitations to the Google Vertex AI and LinkedIn Data Scraper integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by LinkedIn and Google may affect workflow speed.
- Complex AI tasks may require significant processing time.
- Custom code might be needed for advanced data transformations.