Description
This AI-powered workflow automatically extracts company data from LinkedIn using Bright Data and converts it into compelling, publication-ready company stories with Google Gemini. It eliminates the need for manual research, formatting, or writing — delivering structured narratives from just a LinkedIn URL.
👥 Who Is This For
🔍 Researchers & Analysts
To quickly generate structured profiles of target companies
🧲 Sales Teams
To create company summaries for prospecting and outreach
✍️ Content Creators
To auto-generate intros and overviews for company-based content
🧑💻 Startup Founders
To research competitors or industry peers at scale
📢 PR & Marketing Professionals
To craft branded company descriptions for campaigns or press
❗️What Problem Does It Solve
⏳ Manual company research is time-consuming and repetitive
📄 LinkedIn data is unstructured and difficult to summarize
📉 No easy or scalable way to turn profiles into clean narratives
💡 The Solution
This agent automates LinkedIn research and storytelling using scraping + AI:
🔗 Accepts a LinkedIn URL or search term
🛠️ Uses Bright Data to extract raw HTML from the company profile
📄 Parses and retrieves key fields (about, size, industry, HQ, etc.)
🧠 Uses Gemini to write a clean, natural-language company story
📤 Sends the final story via webhook, email, or saves to Notion/Sheets
⚙️ How It Works – The Process
📨 Trigger Input
Receives a LinkedIn company URL or search keyword
🔐 LinkedIn Scraping
Uses Bright Data’s unlocker to extract clean HTML content
🧾 Data Parsing
Pulls structured info like size, industry, HQ, and about section
🧠 AI Story Generation
Gemini writes a concise and compelling narrative
📬 Output Delivery
Sends the output via webhook, email, or to Notion/Google Sheets
✅ Why It Matters
This workflow turns LinkedIn — the world’s largest company directory — into an AI-powered story engine. By combining Bright Data’s scraping capabilities with Gemini’s language generation, it provides a fast, scalable, and zero-effort solution for generating clean company narratives.