I just built an end-to-end AI GTM Automation Engine that fully automates the outbound sales pipeline from lead generation to reply handling

Built with n8n
1

I just built an end-to-end AI GTM Automation Engine that fully automates the outbound sales pipeline from lead gen

automation
automation1663×442 96 KB

eration to reply handling.

This system is designed to remove 90%+ of manual work in B2B outreach and replace it with intelligent automation.

What it does:

Accepts incoming leads via webhook

Enriches and finds emails using multiple providers (Prospeo, Hunter.io, Dropcontact + AI fallback)

Validates emails automatically (NeverBounce)

Scores leads (low / medium / high)

Generates personalized cold emails using AI

Sends outreach via GMAIL

Runs multi-step follow-up sequences (Day 2, 4, 7)

Classifies replies using AI (interested / not_interested / not_now)

Automatically routes actions based on intent

Logs everything into Google Sheets

Sends real-time Slack notifications

Stack:

n8n· OpenAI· @Gmail API · Slack API · Google Sheets · Hunter.io · Dropcontact · NeverBounce

This is part of my deeper focus on building AI-powered revenue systems and GTM automation workflows that replace repetitive sales operations with intelligent agents.

Architecture:

GitHub:

#n8n #automation ai #aiagents #workflowautomation #revops #gtmengineering #salesautomation #leadgeneration #coldemail #emailmarketing #crm hubspot slack #googleworkspace openai #llm #noCode #lowCode #devops #saas #startup #buildinpublic github #python javascript #cloudcomputing #systemdesign #productivitytools

2 Likes
2

Love the end-to-end architecture here — multi-step follow-ups + reply classification is exactly the hard part. Are you seeing consistent falloff across day 2, 4, 7 steps, or does one step drop harder? Also curious how you’re handling hard bounces from the email validators.