AI Phone Agent
Built a 24/7 AI phone agent for a service business with <500ms response time and natural conversation quality.
The Challenge
A regional service business was losing customers during after-hours. Their existing phone system played a voicemail greeting after 6pm — at exactly the moment competitors with 24/7 call centers were capturing those leads. The business estimated 30-40% of their inbound calls came outside business hours, and effectively none of those converted.
They needed 24/7 call handling — but hiring staff wasn't economically viable, and the IVR systems they'd tried felt robotic and drove callers away. They'd tried one off-the-shelf solution six months prior; callers complained the bot sounded scripted, escalation rates were over 70%, and they abandoned it within 30 days.
The requirement was clear: the system needed to sound natural, handle real conversations (not just menu selections), book appointments, answer product questions, and escalate intelligently — all with latency that kept the conversation feeling human. Anything above 1 second of silence between caller and system would kill the experience.
The Solution
We built a real-time AI phone agent using a four-component architecture optimized for latency at every layer. The design principle: each component does one thing well, and the handoffs between components are engineered to minimize wait time. We architected the pipeline so that transcription, inference, and speech synthesis begin as soon as the caller stops speaking — no sequential blocking.
The system was trained on the client's specific business context — services offered, pricing, booking rules, FAQ content, and 200+ edge cases the front desk staff had documented over years of taking calls. We ran three rounds of adversarial testing with a professional voice actor playing difficult callers before go-live.
The system handles full conversations: capturing caller intent, answering questions, booking appointments via calendar API integration, and escalating to human staff when needed (missed payments, complaints, unusual requests).
Technical Details
Key Takeaways
Latency is non-negotiable for voice
In text interfaces, a 2-second delay is annoying. On a phone call, it kills the illusion of natural conversation. We optimized every layer — STT pipeline, model inference, TTS — to stay under 500ms end-to-end.
Escalation design is where most teams underinvest
The AI handles the easy cases. The design of escalation paths — when to hand off, how to transfer context, what on-call staff receives — is what separates a professional deployment from a liability.
Monitor calls, not just metrics
Aggregate metrics (latency, escalation rate) tell you something went wrong. Call transcripts tell you what went wrong. We built transcript review into the operations workflow from day one.
Technology Stack
Client Context
Service business, after-hours coverage gap, losing bookings to competitors with 24/7 availability.
Build something similar?
We've built AI phone agents for several service businesses. Each one is custom — but the architecture is proven.
Get in TouchWant similar results?
Every AI phone agent we build is custom — tuned to your workflow, your customers, and your escalation requirements. Start with a discovery call.