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200k calls/month · 67% booking rate vs 77% human

24/7 AI Agent Call Center: 200k Calls a Month Across 60 US HVAC Brands

Voice agents orchestrating 200,000 calls a month across 60 US HVAC brands for a 5,000-person enterprise, booking 67% of calls against 77% for human agents — within 10 points of a trained team, around the clock. Built as a product, an AI front desk that answers, books and routes, not a pilot.

The problem

For an HVAC brand the front desk is the business: a missed call is a missed booking, and after-hours and peak-hour calls went to voicemail that most callers never leave. Across 60 brands under one 5,000-employee US enterprise, staffing every shift for that volume was hard to justify, and leaving it unanswered cost real business.

What we built

An AI front desk that runs the call centre 24/7: real telephony with barge-in handling so callers can interrupt naturally, booking, rescheduling and cancelling against live availability, answers only from what each brand has approved, and tool-calling into live systems so the agent can look things up and write back rather than just talk.

Before: Night and weekend calls unanswered; Staffing every shift hard to justify; A demo bot is not a call centre. After: 200k calls/month · 67% booking rate vs 77% human.

Before

  • Night and weekend calls unanswered
  • Staffing every shift hard to justify
  • A demo bot is not a call centre

How it works

  1. Answer on real telephony. Callers reach the agent on the phone line and can interrupt it mid-sentence, as they would a person.

  2. Book against real availability. It checks the live calendar, then books, reschedules or cancels directly in the scheduling system instead of taking messages.

  3. Say only what is approved. Questions are answered from what each brand has approved, never improvised.

  4. Hand over with context. When confidence drops, the call moves to a person with the context already written down.

  5. Test on real transcripts. Every release is regression-tested against real call transcripts before it ships.

  6. Trace every call. Each call is traced end to end, so a 3am failure is findable the next morning.

After

200k calls/month · 67% booking rate vs 77% human

Stack

Voice AIAI AgentAI ReceptionistSchedulingTelephonyEnterprise

Why it holds up

Production is a different problem from a demo. This one ships with defined handoff to a human when confidence drops, regression tests over real transcripts before every release, and tracing on every call so a 3am failure is findable the next morning. It is live inside the business, not piloted in a sandbox: 200,000 calls a month across 60 HVAC brands, with a 67% booking rate against 77% for the human team.

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