AI Voice Agent Development

Who this is for

• Businesses missing calls outside office hours
• Teams whose staff spend hours a day on routine phone work — booking, reminders, qualification
• Products adding voice as an interface
• Companies that tried a phone tree and watched callers zero-out to reception

What you get

• A production voice agent on your phone number, inbound or outbound
• Response latency tuned across the whole speech-to-speech pipeline
• Barge-in handling, silence recovery and natural turn-taking
• Warm handoff to a human with a summary of the call so far
• Call recordings, transcripts and analytics
• Integration with your calendar, CRM or booking system

Latency decides everything

A caller will forgive a slightly robotic voice; they will not forgive dead air. Every response travels through speech-to-text, a language model and text-to-speech, and the budget for the whole round trip is about a second before the conversation starts to feel broken. That budget drives every technical decision — streaming at each stage, fast first tokens, short grounded answers — and it is the main reason voice agents are engineered rather than configured.

Built for how people actually talk

Real callers interrupt mid-sentence, go quiet while they find their card, mumble, and change their mind halfway through a booking. A production agent handles barge-in by stopping immediately when the caller speaks, recovers from silence without repeating itself verbatim, and confirms the details that matter — names, dates, numbers — instead of assuming the transcription was right. Testing happens with real calls, accents and background noise, not just happy-path transcripts.

The handoff is part of the product

Some calls should reach a human, and the agent's job is to know which ones and to hand them over well. That means a warm transfer with a summary of the conversation so far — who is calling, what they need, what has already been checked — so the caller never repeats themselves. An agent that owns the routine sixty percent of calls completely and escalates the rest cleanly beats one that attempts everything and does half of it badly.

Platform where it fits, custom where it doesn't

Vapi and Retell AI handle telephony, turn-taking and interruptions out of the box, which makes them the right default for phone-based agents. A custom pipeline earns its keep when a platform's constraints or per-minute pricing don't fit the use case — the AI voice agent for education in the case studies runs on a direct pipeline built on the Gemini API for exactly that reason. The choice is made against your latency, language and cost requirements, not by habit.

How the engagement works

1. 01

   Discovery

   Map the call flows worth automating and the ones that must reach a human immediately. An agent that owns the routine calls completely beats one that attempts everything.

2. 02

   Design

   Script the conversation states, interruptions and failure paths, and choose the platform against your latency, language and integration needs.

3. 03

   Build

   Implement, then test with real calls — accents, background noise, people talking over the agent — not just happy-path transcripts.

4. 04

   Ship

   Go live with recordings, transcripts and analytics, plus 24-hour response times for 30 days after launch.

Technology

Platforms

Vapi and Retell AI for production telephony — turn-taking, barge-in and phone infrastructure handled; ElevenLabs where voice quality is the differentiator.

Custom pipelines

Direct speech-to-text → LLM → text-to-speech builds, as in the education voice agent on the Gemini API, where platform constraints or per-minute pricing don't fit.

Intelligence

The same discipline as chat: retrieval over your data, schema-validated actions, explicit refusal and escalation rules.

Integration

Calendars, CRMs and booking systems via API, so the agent completes tasks instead of taking messages.

Proof

Frequently asked