Building my first AI lead generation SaaS (LeadIt) — MVP architecture

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:

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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

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Workflow

The flow of the system is roughly:

1. User searches for companies
2. Scraper collects company data
3. Signals detection analyzes companies
4. AI generates personalized outreach emails
5. Emails are sent and tracked using Gmail API
6. Data is stored in Supabase

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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.

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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!