When you're running eight concurrent AI voice agents across residential and commercial properties, you need infrastructure that doesn't break. We built the Quiet Hours Valet Command Center—a production-grade dispatch system handling real-time voice interactions, automation workflows, and client management—entirely on Supabase Edge Functions, VAPI's voice API, and a self-hosted Postgres schema. This article walks through the technical architecture: how we structured an 8-table relational schema to track voice agent states, built five frontend pages on Vercel to manage 8 automation scenarios, and engineered Supabase Edge Functions as webhook handlers for asynchronous VAPI call processing. If you're integrating AI voice APIs into a scaling SaaS or operations platform, this breakdown covers the exact patterns that let us go from prototype to production handling real customer interactions.
Domonique Luchin
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