OPENING PARAGRAPH:
We built Quiet Hours Valet's command center in 60 days: 8 concurrent AI voice agents orchestrated through VAPI, backed by a custom Postgres schema across 8 tables, with real-time webhook processing via Supabase Edge Functions. This isn't a chatbot—it's a production dispatch system handling valet operations, customer routing, and service automation at scale. Here's how we architected it: frontend deployed to Vercel, VAPI agents handling natural language intent routing, Asterisk PBX integration for legacy phone systems, and a Supabase database layer managing agent state, conversation logs, and automation triggers. If you're building voice-first infrastructure for service businesses or wrestling with how to wire VAPI webhooks into a reliable backend, this breakdown covers the schema design decisions, Edge Function patterns, and deployment strategy that let us go from zero to production without overhauling infrastructure.
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