How we scaled a Voice AI SaaS to $7k MRR with 21 clients using n8n + Supabase (Seeking Technical Lead)

I wanted to share a breakdown of how we validated and scaled our Voice AI service. We just hit a milestone of $7,000 MRR with 21 active clients, and we did it almost entirely through a high-level No-Code/Low-Code orchestration.

Website: restorationai.io Company: Restoration AI

The Stack:

• Orchestration: n8n (This is our engine room—handling all voice routing and API logic).
• Logic/Brain: Gemini AI Studio (We use the long-context window to ingest API docs for custom logic generation).
• Backend: Supabase (Auth, DB, and data flow).

The Situation: We’ve proven the market and the growth is consistent. However, as we scale past 21 clients, the complexity of our n8n workflows is reaching a point where we need a dedicated Technical Lead. We’re moving from "vibe-coded" MVP to production-grade architecture.

What we’re looking for:

• n8n Expert: You should be a wizard with sub-workflows, managing complex OAuth scopes, and error handling.
• SaaS Mindset: You understand how to build for reliability and multi-tenant scaling.
• Stack Comfort: High comfort level with Supabase and using LLMs to accelerate development.

The Deal: We are 100% bootstrapped, profitable, and growing. This is a chance to join a moving train with real cash flow. We are looking for a long-term partner; potential equity is on the table as we hit our next growth milestones.

Let's Talk: I’m happy to answer any questions about our build process, how we’re using Gemini as an "IDE," or how we structured the initial voice routing in n8n!

If you’re a builder who wants to help take this to $50k MRR, DM me with your background and the most complex automation you’ve ever built. 🤙