Building a Multi-Agent Voice Command Center: Supabase Edge Functions, VAPI, and Real-Time Automation at Scale

We built Quiet Hours Valet's command center from scratch—5 frontend pages orchestrating 8 concurrent AI voice agents, 8 automation workflows, and an 8-table Postgres schema—all running on Supabase Edge Functions and VAPI webhooks. This article breaks down the architecture decisions, the webhook-to-automation pipeline that powers our valet trash operation, and how we use Supabase's serverless compute layer to route customer calls into parallel agent workflows without managing a single server. If you're building voice-first SaaS, integrating real-time AI agents with a relational database, or trying to scale Asterisk PBX infrastructure without losing your mind, this technical deep-dive covers the routing logic, schema design, and deployment strategy we used to move from local development to production on Vercel.