AI Cold Outreach & Lead Generation System (n8n + AI) I built an automated system that finds leads...AI Cold Outreach & Lead Generation System (n8n + AI) I built an automated system that finds leads...
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AI Cold Outreach & Lead Generation System (n8n + AI)
I built an automated system that finds leads, writes personal emails, and follows up, without manual work.
The problem
Cold outreach takes hours every day. Finding leads, researching each one, writing emails, tracking replies, and following up. It is slow and easy to mess up.
What I built
A single n8n system that runs the full outreach process on a schedule.
Finds new leads from Apollo every morning
Enriches and researches each lead using web scraping and AI
Keeps only qualified leads, then saves them to a Google Sheet
Waits for human approval in the sheet before anything sends
Uses AI to write a personal email for each approved lead
Sends safely with delays between emails to protect deliverability
Detects replies automatically and notifies the client
Sends smart follow-ups to leads who did not answer
The smart part
Nothing sends without approval. A person reviews leads in the sheet first. This keeps the sending safe and avoids spam problems. It also has built-in error alerts, so if anything breaks, I get notified right away.
Tech used
n8n, Apollo, Firecrawl, Google Gemini, Google Sheets, IONOS email (SMTP and IMAP).
Result
A hands-off outreach engine that turns cold lead hunting into an automatic daily process, with a human in control of what goes out.
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Polar is a local, privacy-focused AI desktop assistant designed around a futuristic HUD interface and system-level interaction.
The project explored how a desktop AI could understand the user's environment, process visual and voice input, and respond or perform actions without relying entirely on cloud services.
Key features:
Local AI assistant architecture
Futuristic Tauri-based desktop HUD
Screen and contextual awareness
OCR-based extraction of text from the screen
Voice interaction pipeline
AI-powered context processing and responses
System-level desktop interaction and automation
Local/offline model execution
Real-time assistant-style interface
OCR pipeline:
Screen capture → OCR → Context extraction → Local AI → Response/Action → HUD
The project combined AI, computer vision, OCR, voice interaction, desktop application development, and modern UI engineering into a single experimental personal-assistant platform.
My contribution: Architecture, application development, AI integration, OCR functionality, UI/HUD development, and system interaction.
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