This n8n workflow automates the discovery, enrichment, and comparative analysis of startups from the Crunchbase dataset via Bright Data, enhanced with AI, and exports structured results to Google Sheets.
🚀 What It Does
Receives a keyword from the user that describes the area of interest — such as an industry, sector, technology, or trend (e.g., "AI in healthcare", "carbon capture", "edtech").
This keyword is used to filter relevant startups from the Crunchbase dataset via Bright Data.
Fetches data from Bright Data's Crunchbase snapshot API.
Extracts and cleans key fields from the JSON response.
Sorts startups by most recent founding date.
Selects the top 10 most recent companies.
Sends these 10 companies to Google Gemini AI for comparative analysis.
Embeds the AI-generated summary into the final export.
Appends results to a Google Sheet for tracking and reporting.
🛠️ Step-by-Step Setup
🧠 How It Works
📤 Google Sheet Output
Each row includes:
name,
founded,
about,
num_employees,
type,
ipo_status,
full_description,
social_media_links,
address,
website,
funding_total,
num_investors,
lead_investors,
founders,
products_and_services,
monthly_visits,
crunchbase_link,
ai_analysis.
AI comparative analysis summary (only once per batch – attached to the first company).
All fields from above customizible through the python code (you can add additional ones from Bright Data output).
🔐 Required Credentials
⚠️ Notes