Hi everyone 👋
I'm currently building my first SaaS product called LeadIt.
The idea behind LeadIt is simple:
Quality over quantity in lead generation.
Instead of scraping thousands of random leads, the system tries to identify companies that actually show signals of being a good fit.
This is still an MVP, and I'm trying to keep the architecture simple while validating the idea.
Here is the architecture I designed for the MVP:
Tech Stack
Frontend
- Next.js UI
Backend
- Next.js server API
Authentication
- Google OAuth 2.0
Lead Analysis Modules
- Scraper using Playwright
- Web intelligence using Tavily API
- Signals detection (job listings, API docs, integration pages)
- AI-generated outreach emails
AI Layer
- Groq for LLM processing
Data Layer
- Supabase database
Outreach
- Gmail API for sending emails
Workflow
The flow of the system is roughly:
- User searches for companies
- Scraper collects company data
- Signals detection analyzes companies
- AI generates personalized outreach emails
- Emails are sent and tracked using Gmail API
- Data is stored in Supabase
Why I'm building this
I noticed that most lead generation tools focus on volume, not relevance.
The goal of LeadIt is to find high-quality opportunities instead of sending thousands of cold emails.
Feedback welcome 🙏
Since this is still an MVP, I’d love feedback from other builders:
- Does this architecture make sense?
- Am I overengineering anything?
- What would you simplify?
I'm building this in public, so I'll keep sharing progress as I go.
Thanks!
Top comments (1)
Great MVP architecture, Kumar! I really like the focus on quality over quantity — most lead gen tools just optimize for volume and it burns through sender reputation fast.
One thing you might consider adding: a social listening layer. We've found that the highest-converting leads come from people who are actively asking for recommendations on platforms like Reddit, rather than cold scraping. They're pre-qualified because they're literally saying "I need a tool that does X."
We use Rixly (userixly.com) to monitor conversations across Reddit/LinkedIn for buying intent signals — it catches people asking for recommendations in relevant subreddits and suggests contextual replies. The conversion rates from warm outreach on those threads are significantly higher than cold email.
For your MVP though, the architecture looks solid. Playwright + Supabase is a proven combo. My only suggestion would be to add an intent-scoring layer early so you can prioritize which leads are worth the personalized email effort. Good luck with the launch!