Automate Company Story Generation with LinkedIn, Bright Data & Google Gemini

What This Automation Does

This workflow scrapes LinkedIn company data using Bright Data and turns it into neat company stories with Google Gemini AI.
It handles scraping, waiting for data ready, extracting key details, and making short summaries.
The output goes to webhooks for easy use in other apps.
This saves time, stops errors, and makes story results consistent every time.

Tools and Services Used

• n8n: Automation platform to build and run the workflow.
• Bright Data API: Triggers LinkedIn scraping and fetches data snapshots.
• Google Gemini AI: Converts extracted LinkedIn data into human-like stories and summaries.
• Webhook service: Receives final story and summary notifications for downstream use.

Who Should Use This Workflow

This is for people who need regular LinkedIn company stories fast.
Users with basic n8n experience who want to avoid manual scraping and story writing.

Inputs, Processing, and Outputs

Inputs

• LinkedIn company page URL
• Bright Data API key and dataset ID
• Google Gemini API credentials
• Webhook URL for notifications

Processing Steps

• Trigger scraping with Bright Data using the company URL.
• Store snapshot ID from Bright Data response.
• Poll Bright Data progress endpoint until data is ready.
• Download the JSON snapshot of scraped LinkedIn data.
• Use LangChain node with AI to extract structured company info.
• Generate a detailed company story using Google Gemini.
• Generate a short summary from the detailed story.
• Send the story and summary to configured webhook endpoints.

Outputs

• Detailed company story text
• Concise summary text
• Webhook notifications delivering the above

Beginner Step-by-Step: How to Use in n8n Production

Step 1 – Import Workflow

1. Download the workflow file using the Download button on this page.
2. Open the n8n editor.
3. Select "Import from File" and upload the downloaded workflow JSON.

Step 2 – Configure Credentials

1. Open the Perform LinkedIn Web Request node and enter your Bright Data API Key in the authentication header.
2. Open Google Gemini Chat Model nodes and enter your Google PaLM API credentials.

Step 3 – Update Settings

1. In Set LinkedIn URL, set the company LinkedIn URL to the target company.
2. If using different webhook receivers, update URLs in the webhook notifier nodes.

Step 4 – Test Workflow

1. Click "Execute Workflow" in the n8n editor to run it once manually.
2. Check for errors in each node output and correct credentials or URLs if needed.

Step 5 – Activate Workflow

1. Turn on the workflow toggle in the top-right corner to activate.
2. Optionally, schedule automatic runs via cron or webhook triggers.

If using self hosting n8n, refer to self-host n8n for server setup advice.

Common Problems and Solutions

Problem: 401 or 403 Errors Calling Bright Data API

Cause: API Key is wrong or headers are misconfigured.

Fix: Double-check the Bright Data API Key in Perform LinkedIn Web Request node. Use correct header format.

Problem: Snapshot Status Not Changing to Ready

Cause: Snapshot ID is missing or API took longer than wait time.

Fix: Ensure Set Snapshot Id maps snapshot ID properly. Increase wait time in Wait for 30 seconds node.

Problem: AI Story Output Is Incomplete or Off-Topic

Cause: The system prompt or input data is wrong.

Fix: Edit prompt in LinkedIn Data Extractor node. Confirm the input JSON has full LinkedIn data.

Problem: No Webhook Notification Received

Cause: Incorrect webhook URL or API failure.

Fix: Check webhook URLs in notifier nodes. Confirm webhook endpoint is active and reachable.

Customization Ideas

• Make LinkedIn URL dynamic by replacing hardcoded URL with a webhook trigger or environment variable.
• Change wait duration in the Wait for 30 seconds to fit larger sites or API limits.
• Improve story style by editing the systemPromptTemplate in the LinkedIn Data Extractor node to sound formal or casual.
• Replace webhook notifier nodes with nodes for Slack or email to send stories directly to teams.
• Test other Google Gemini models by changing model names in Google Gemini Chat Model nodes.

Summary

✓ saves hours by automating LinkedIn data collection and story creation
✓ reduces errors by automating data checks and waiting
✓ creates consistent, readable company stories and summaries
✓ delivers ready content via webhook notifications
✓ simple to test and activate inside n8n editor