How I Built a Cold Outreach SaaS with AI – and You Can Too (Full Stack Breakdown)

Are you a developer dreaming of building your own AI-powered SaaS but unsure where to start? In this post, I’ll walk you through how I built ColdMail AI, a cold outreach SaaS that uses artificial intelligence to generate high-converting cold emails and how you can do the same.

Why Cold Outreach SaaS?

Cold emailing remains one of the most effective B2B marketing strategies. By combining it with AI, we eliminate guesswork and scale personalization effortlessly. ColdMail AI was built to solve this exact problem.

Tools & Stack I Used

• Frontend: React + TailwindCSS

• Backend: Node.js + Express

• Database: MongoDB (Atlas)

• AI Engine: OpenRouter API using Mixtral for cold email generation

• Deployment: Vercel (frontend) + Render (backend)

• Automation: Cron jobs for scheduling

Key Features

• Auto-generates personalized cold emails

• Saves and categorizes contacts

• Email templates based on industry

• Analytics dashboard for opens/clicks

Building It: Step-by-Step

• MVP Planning: Defined the core value — fast, high-converting email generation

• Wireframes: Designed 3 core pages — Email Composer, Contacts, Analytics

• Frontend Setup: Used Tailwind for fast styling and responsiveness

• OpenRouter API Integration: Prompted Mixtral with dynamic fields like name, industry, offer

• Database Schema: Simple collections for Users, Leads, Templates, Campaigns

• Authentication: JWT-based with role distinction (Admin/User)

• Email API: Used Resend for transactional & marketing emails

• Analytics: Tracked open/click events via webhook callbacks

Lessons Learned

• LLMs work best when given structured prompts

• Caching AI outputs reduces costs

• User onboarding must be dead simple

You Can Build This Too

Clone a simple boilerplate, hook up a local LLM (or use OpenRouter), and start solving one real problem. ColdMail AI is proof that solo devs can still win in 2025.

👉 https://x.com/LabsAix