Phone calls answered and placed by an agent that actually holds a conversation. It books, looks things up, updates your systems, and hands to a person the moment it should.
Trusted by teams worldwide
Voice is unforgiving. A caller hears every pause and every wrong turn, so most of the work is in the parts nobody demos. Assistants that answer in text belong with AI chatbot development.
The difference between a demo and a deployment is almost entirely in these six.
Callers interrupt, trail off and change their mind mid-sentence. We tune barge-in and end-of-speech detection for that, because an agent that talks over people is worse than a menu.
Speech becomes an intent and a set of parameters, not a keyword match. The caller says it their way and the agent still gets to the right task.
Checking a calendar, booking a slot, looking up an order, updating a record. Answering is the easy half; completing the task is what removes the call from a human queue.
Confidence thresholds, sensitive topics and frustrated callers all trigger a transfer, with context attached. Knowing when to stop is a feature.
Disclosure, consent capture, retention limits and audit trails agreed before build. In regulated calls these are requirements, not settings to add later.
Containment, handover rate, task completion and what callers asked that nobody anticipated. Quality becomes a number you can act on.
Most projects are one of these eight. The right one is usually obvious once the call recordings are on the table.
Each turn is a full round trip, repeated for the length of the call. Our guide to building an AI voice agent goes deeper.
Send us a week of call reasons, or just describe what your team answers all day. We will tell you which calls a voice agent should take, which it should never take, and what has to exist before either is true.
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Five phases. The listening phase is the one people want to skip and the one that decides the outcome.
We go through real call recordings and reasons with your team, and agree which intents are in scope and which are explicitly out.
Call flow, escalation rules, disclosure wording, data handling and the success measure, agreed before anything is built.
One intent on one number, running alongside your existing setup, so the runbook is proven on something low-risk.
Rolled out intent by intent with a human queue behind it, and a rollback path kept open throughout.
Transcripts reviewed against the test set, prompts and routing adjusted, then handover to your team.
Figures below come from one named, published deployment rather than a blended average.
The starting position in that same deployment, which is what the agent was built to fix.
No queue, no voicemail and no out-of-hours gap.
Across Appther's delivery, with voice tuned per market and language.
Chosen per deployment. Speech vendors in particular are picked per language rather than standardised for convenience, and we will say so when a simpler tool is the right answer.
The same agent behaves very differently by sector. These are the calls each one usually automates first.
Patient intake, booking and rescheduling, without touching clinical advice.
Account and card calls inside strict authentication and audit requirements.
Order and returns calls answered from live order data.
Enquiry qualification and viewing booking outside office hours.
Admissions and student services calls at the times they actually spike.
Delivery status and scheduling calls, plus support for drivers and technicians.
Any number quoted before the call flow is understood is a guess. These are the things that actually move it. For worked ranges see our voice agent cost breakdown.
“Appther built our student competition app exactly the way we envisioned it: easy registration, smooth judging, and real-time results that keep participants engaged.”
“Building a mental health app means every detail has to be handled with care, and Appther got that from day one. The product feels warm, simple, and genuinely helpful.”
“Appther exceeded every expectation, on time and on budget, and the final product has been instrumental in scaling our business. A rare engineering partner.”
“Implementing an ERP across our operations felt daunting at first, but Appther made the transition seamless. Every department now works off a single source of truth.”
Field notes from real deployments. No hype, just what worked and what didn't.
A complete business guide, from call flow to go-live.
Where the money goes, and what changes between the two.
The failure modes we design around before writing a prompt.
Salesforce, HubSpot and Odoo, with the gotchas.
Tell us what your team answers all day and we will tell you what a voice agent should take, what it should never take, and what has to be true before either works.
Tell us what you want your chatbot to do. No sales pitch, just a straight answer on scope, timeline and cost.
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