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Muro-AI Automation Hub

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Vapi + n8n: Creating an Automated AI Voice Agent
Most Detailing Shops Don’t Have a Quality Problem — They Have a Phone Problem I recently tested a Vapi-powered AI voice agent with a detailing shop, and it revealed something interesting: The biggest bottleneck wasn’t the detailing work itself — it was missed or delayed phone calls. When the team is working on cars, they simply can’t answer every call. That leads to missed leads, slower follow-ups, and inconsistent booking flow. To understand the impact, we let an AI agent handle: Basic lead qualification Appointment scheduling Follow-up calls Simple customer queries What Actually Improved The team saved around 15 hours per week Follow-ups became consistent Missed-call bookings increased noticeably The shop stayed focused on actual detailing work Why share this? A lot of service businesses underestimate how much revenue disappears due to unmanaged calls. This experiment showed how a lightweight AI voice layer can stabilize communication without adding extra workload or staff. If anyone here is exploring AI for operations or wants insights on the setup, I’m happy to share what I learned.
Vapi + n8n: Creating an Automated AI Voice Agent
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