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Generate company stories from LinkedIn with Bright Data & Google Gemini

Ranjan DailataRanjan Dailata
1047 views
2/3/2026
Conditional LogicUser ManagementData ValidationCRM IntegrationAPI Automation
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Who this is for?

The LinkedIn Company Story Generator is an automated workflow that extracts company profile data from LinkedIn using Bright Data's web scraping infrastructure, then transforms that data into a professionally written narrative or story using a language model (e.g., OpenAI, Gemini). The final output is sent via webhook notification, making it easy to publish, review, or further automate.

This workflow is tailored for:​

  • Marketing Professionals: Seeking to generate compelling company narratives for campaigns.​

  • Sales Teams: Aiming to understand potential clients through summarized company insights.​

  • Content Creators: Looking to craft stories or articles based on company data.​

  • Recruiters: Interested in obtaining concise overviews of companies for talent acquisition strategies.​

What problem is this workflow solving?

Manually gathering and summarizing company information from LinkedIn can be time-consuming and inconsistent. This workflow automates the process, ensuring:​

  • Efficiency: Quick extraction and summarization of company data.​

  • Consistency: Standardized summaries for uniformity across use cases.​

  • Scalability: Ability to process multiple companies without additional manual effort.

What this workflow does

The workflow performs the following steps:​

  • Input Acquisition: Receives a company's name or LinkedIn URL as input.​

  • Data Extraction: Utilizes Bright Data to scrape the company's LinkedIn profile.​

  • Information Parsing: Processes the extracted HTML content to retrieve relevant company details.​

  • Summarization: Employs AI Google Gemini to generate a concise company story.

  • Output Delivery: Sends the summarized content to a specified webhook or email address.

Setup

  • Sign up at Bright Data.
  • Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.
  • In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). Header Authentication.png The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token.
  • In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy).
  • Update the LinkedIn URL by navigating to the Set LinkedIn URL node.
  • Update the Webhook HTTP Request node with the Webhook endpoint of your choice.

How to customize this workflow to your needs

  • Input Variations: Modify the Set LinkedIn URL node to accept a different company LinkedIn URL.

  • Data Points: Adjust the HTML Data Extractor Node to retrieve additional details like employee count, industry, or headquarters location.​

  • Summarization Style: Customize the AI prompt to generate summaries in different tones or formats (e.g., formal, casual, bullet points).​

  • Output Destinations: Configure the output node to send summaries to various platforms, such as Slack, CRM systems, or databases.

Generate Company Stories from LinkedIn with Bright Data & Google Gemini

This n8n workflow automates the process of extracting company information from LinkedIn using Bright Data, then uses Google Gemini to generate compelling company stories based on the extracted data. It's designed to streamline content creation for marketing, sales, or internal communication purposes.

What it does

This workflow simplifies and automates the following steps:

  1. Manual Trigger: The workflow is initiated manually, allowing you to control when the process starts.
  2. HTTP Request: It makes an HTTP request, likely to an API endpoint (e.g., Bright Data) to fetch company data from LinkedIn.
  3. Wait: Introduces a pause, potentially to allow the external data fetching service to complete its operation or to respect API rate limits.
  4. Edit Fields (Set): Transforms or prepares the data received from the HTTP request for further processing.
  5. If: A conditional check that likely determines if the data extraction was successful or if certain criteria are met before proceeding.
  6. Default Data Loader: Loads the processed data into a format suitable for language model processing.
  7. Recursive Character Text Splitter: Splits the loaded text into smaller, manageable chunks, which is crucial for processing large documents with language models.
  8. Information Extractor: Uses a language model (likely Google Gemini) to extract specific, structured information (e.g., company details, achievements, key personnel) from the text.
  9. Google Gemini Chat Model: Leverages Google Gemini as the language model to process the extracted information.
  10. Summarization Chain: Generates a concise and compelling company story based on the extracted and processed information.
  11. Sticky Note: Provides a place for notes or comments within the workflow, likely for documentation or explanation of a specific step.

Prerequisites/Requirements

To use this workflow, you will need:

  • Bright Data Account: An account with Bright Data (or a similar web scraping service) configured to extract LinkedIn company profiles.
  • Google Gemini API Key: Access to the Google Gemini API for natural language processing and generation.
  • n8n Instance: A running instance of n8n.

Setup/Usage

  1. Import the workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure Credentials:
    • HTTP Request (Node 19): Update this node with your Bright Data API endpoint, API key, and any necessary parameters for LinkedIn company data extraction.
    • Google Gemini Chat Model (Node 1262): Configure your Google Gemini API key within this node's credentials.
  3. Adjust 'Edit Fields (Set)' (Node 38): Modify this node to correctly parse and prepare the data structure returned by your Bright Data setup for optimal input into the AI models.
  4. Review 'If' (Node 20): Customize the conditions in this node based on your data validation requirements.
  5. Execute the workflow: Click the "Execute workflow" button on the "Manual Trigger" node to run the workflow.

The generated company stories will be available in the output of the "Summarization Chain" node.

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