This project was developed as part of the Caprae Capital AI Readiness Challenge by Kavya Bhardwaj.
It is a smart, automated tool to extract structured company data (leads) using a mix of APIs, Regex, and AI models.
Given a list of company names, it fetches:
- 🌐 Official Website (via Serper API)
- 📧 Emails (via Hunter.io and website scraping fallback)
- 👤 CEO Name (via DataForSEO SERP + Hugging Face AI QA model)
- 🔗 LinkedIn URL (via Google SERP matching)
- 💰 Revenue Estimates (regex from live SERPs + AI fallback)
- 👥 Employee Estimates (regex logic + Hugging Face fallback)
- 📁 Exports everything to a downloadable
.csv
| Data Field | Powered By |
|---|---|
| Website | ✅ Serper API |
| Emails | ✅ Hunter.io API, ✅ Regex (fallback) |
| CEO Name | ✅ DataForSEO API + 🤖 Hugging Face AI |
| LinkedIn Profile | ✅ DataForSEO API |
| Revenue | ✅ DataForSEO API, Regex, 🤖 Hugging Face AI |
| Employees | ✅ DataForSEO API, Regex, 🤖 Hugging Face AI |
- ✅ Regex + AI fallback pipeline
- ✅ Fallback email scraping using
BeautifulSoup - ✅ Range filtering for employees (e.g., 1K–1M)
- ✅ Currency-aware parsing (USD, INR, Crore)
- ✅ Retry logic for missing data
- ✅ Fully exportable CSV
| Company | CEO | Revenue | Employees |
|---|---|---|---|
| Apple | Tim Cook | $391.04B | ~164,000 |
| Zomato | Deepinder Goyal | ₹12,114 Cr | ~4,000 |
| Sundar Pichai | $350.02B | ~183,000 |
- Install requirements:
!pip install transformers beautifulsoup4 requests-
Paste the code into a Google Colab or local Python script
-
Run:
companies = ["Apple", "Google", "Zomato"]
results = process_companies(companies)- Export CSV:
import pandas as pd
pd.DataFrame(results).to_csv("lead_results.csv", index=False)Feel free to connect:
Built with 💡 by Kavya Bhardwaj