The cost to build an AI voice agent splits into a one-time build and ongoing per-minute run costs. Here is what actually drives each.
A production AI voice agent has two cost buckets: a one-time build and ongoing run costs. A focused build wired into your live systems typically runs in the low-to-mid five figures USD; the drivers are how many call types you automate, how deep the integrations go, and how many languages you support. Run costs are per-minute and stack telephony, speech-to-text, the language model, and text-to-speech, usually landing around a few US cents to low tens of cents per minute at production volume. We scope to a fixed outcome and quote before we start, then give you an honest per-minute estimate at your call volume, the same methodology behind our full cost breakdown. No open-ended hourly meter.
The single biggest cost lever is integration depth. An agent that only answers FAQs is cheap; an agent wired into your CRM, scheduling system, and billing to actually resolve calls is where the engineering goes and where the value is. That same integration depth is also the biggest factor in how long a build like this takes.
Run costs scale with usage, not headcount, which is the whole point: in the voice agent proof of concept we built for Battery Smart, in-scope calls were resolved end to end without adding headcount, so cost per resolved call falls as volume rises instead of climbing with every new hire. The same fixed-scope pricing logic applies to workflow automation projects too.
Most of these come up during a process diagnostic: a fixed-price session where we map your specific case. Book one and get a straight answer from the engineer who builds these systems, not a sales rep.