I built my own lead generation machine because I moved to Denmark with zero network.

I moved to Denmark.

I didn't know anyone. I had no network. And I needed to find companies I could sell automation services to.

I could spend hours manually searching for companies, finding emails, cleaning data, and sending messages one by one.

Or I could automate the process.

So I built a complete lead generation pipeline:

→ 🐍 Python scraper connected to Denmark's public government CVR database → 📊 Google Sheets synchronization to normalize and deduplicate companies → ✉️ Automated cold email workflow with 10 sector-specific templates using n8n → 📱 Daily Telegram reports with full pipeline statistics → 💼 Assisted LinkedIn outreach: 10 leads per day + a ready-to-send message

And these are the numbers:

📈 19,334 leads in the database 📧 71% email coverage 🏭 10 sectors 🔢 34 industry codes ✉️ 25 automated emails per day ♾️ ~534 days of outreach without repeating a lead 💰 $5/month total cost — basically just the VPS.

The interesting part isn't the scraper.

It's not n8n.

It's not Telegram.

The interesting part is that a process that used to take hours of manual work can now run almost entirely on its own.

And that's exactly what I want to build for companies:

Find repetitive processes → design the system → automate them → measure the results.

In the video, I break down the entire pipeline, piece by piece.

If you're building something similar, let me know which part you'd like me to break down next. 👇

#Automation #AI #LeadGeneration #n8n #Python #ColdEmail #SalesAutomation #B2BAutomation #Denmark #BuildInPublic

Really impressive system. The part that caught my attention is the automated cold email workflow.

Once you start scaling the volume, keeping deliverability consistent across domains and inboxes becomes just as important as the automation itself. Great build!

🚀 Building My AI Lead Generation Agent with n8n

Good Work