AI Voice Agents
Calls go unanswered after hours and hiring more phone staff does not scale. A voice agent only helps if it survives latency, interruptions and the moment it has to hand off - the three things demos skip.
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- What we build: production voice agents with a latency budget, barge-in handling and a defined handoff.
- Who for: ops and CX leads at any business with high inbound call volume.
- In what timeframe: a scoped PoC scored against a real-call scenario suite before it goes live.
Why most ai voice agents projects fail in production
No latency budget
Each hop - transcription, inference, speech synthesis - adds delay, and an unbudgeted pipeline crosses the point where the caller hears a pause and disengages.
No barge-in handling
Real callers interrupt. An agent that finishes its scripted line while the caller is talking reads as a machine and gets escalated immediately.
No handoff rule
Every voice agent hits a request it cannot complete. Without a defined threshold and a warm handoff, it either stalls or confidently does the wrong thing.
How we build ai voice agents
Latency-first pipeline
We budget round-trip time at design and choose transcription, model and TTS to fit it, with a fallback path when a hop is slow.
Turn-taking & barge-in
The agent yields the moment the caller speaks, re-listens, and tracks intent across interruptions rather than replaying a script.
Grounded responses
Answers are grounded in your own content and account data, so the agent is accurate on your specifics, not just fluent in general.
Handoff & escalation
A confidence threshold and authorisation rules decide when a human takes over, with full call context passed along.
How we measure it
A demo passes once. Production passes ten thousand times. Every build ships with an eval harness scoring against a baseline before it goes near a user.
Where the agent stops
Handled end-to-end
- Answering routine inbound questions after hours
- Booking, rescheduling and confirming appointments
- Capturing and qualifying lead details
- Routing to the right team with context
Always goes to a human
- Anything below the confidence threshold
- Requests it is not authorised to complete
- Any explicit request for a person
- Payment or account changes
Stack
Model-agnostic by default, with a fallback path and cost controls wired in — we pick per use case on latency, cost and data-handling, not a default vendor.
Industries where this pays off
Benchmark in progress
A published latency-and-completion benchmark for a reference voice build is in progress - and until it exists we will not quote a number we cannot reproduce. What we can show today is the architecture: a budgeted latency pipeline, barge-in handling and a hard handoff rule, evaluated against a real-call scenario suite before anything goes live. Scope a PoC and the first deliverable is that eval on your own call types.
FAQ
Why do most AI voice agents fall apart on real calls?
Three things a demo never tests: latency, interruptions and handoff. A caller will not wait two seconds for a reply, will talk over the agent, and will occasionally need something the agent cannot do. If the build has no latency budget, no barge-in handling and no hard handoff rule, it sounds fine in a scripted demo and fails on the first real call. We build those three first.
What is an acceptable response latency for a voice agent?
Round-trip latency - speech-in to speech-out - needs to stay low enough that the caller does not perceive a pause, which in practice means budgeting every hop: transcription, model inference, and text-to-speech. We set a latency budget at design time and measure against it in the eval harness, because a correct answer that arrives two seconds late still reads as a broken call.
Can the agent handle being interrupted mid-sentence?
Yes - barge-in handling is a first-class requirement, not a nice-to-have. The agent stops speaking when the caller starts, re-listens, and picks up the new intent rather than finishing its scripted line. Without it the agent talks over people, which is the single fastest way a caller loses trust and asks for a human.
When does the agent hand off to a person?
On a defined rule, not a guess. Anything below a confidence threshold, any request the agent is not authorised to complete, and any explicit ask for a human triggers a warm handoff with the full call context passed along, so the caller does not repeat themselves. The handoff rule is the product decision that makes a voice agent safe to put on your main line.
How do you measure whether the voice agent is good enough to ship?
Against a scenario suite built from real call types, scored before it goes live: task-completion rate, latency, false-handoff and missed-handoff rates, and transcription accuracy on your vocabulary. It ships when it clears the baseline on that suite, and every prompt or model change is re-scored against it - so improvements are measured, not assumed.
Which industries get the most value from a voice agent?
Any business with high inbound call volume where calls go unanswered after hours and adding phone staff does not scale - dealership service lines, field-service dispatch, and dental or clinic front desks are common. Those are the verticals where a missed call is a lost customer and a voice agent that handles the routine calls pays for itself quickly.
See it pass an eval, not a demo.
A scoped PoC with the eval harness attached — timeline and scope on the call, no price on the page.
Scope an AI PoC →