AI voice collections, owned by the client.
A complete outbound collections voice stack for a fintech in Uruguay — built under their brand, transferred to their name. It replaced a 40-person dialing operation in six weeks. By week two, the agent was already outperforming the team it replaced.
Forty people, dialing all day.
Recovery ran on a floor of forty collectors working a dialer by hand. Most of the day went to dead ends — voicemails, no-answers, wrong numbers — and the few real conversations followed whatever script each agent remembered that morning. Output rose and fell with mood, tenure, and turnover.
For a fintech, recovery is margin. Every account that slips past its window costs more to collect and is less likely to pay at all. The operation was expensive, hard to scale, and impossible to keep consistent across delinquency buckets — and there was no clean record of what actually worked on a call.
A full voice stack, under their brand.
Not a chatbot bolted onto a phone line. The complete outbound collections engine — scripts, filtering, scoring, and timing — built to run their book end to end.
A different conversation per bucket
Scripts that shift by delinquency stage — early reminders, firm negotiation, payment-plan offers — and adapt live to what the debtor says, instead of one rigid flow for every account.
Talk to people, not voicemail
Answering-machine detection screens out voicemails, dead lines, and dial tones before the agent says a word — so effort lands on real, live conversations.
Every call scored, not sampled
Each call is transcribed and scored automatically — tone, compliance, outcome — so quality is measured on the whole book, not a handful of spot-checks.
The right call at the right hour
Retry logic and calling windows decide who to call back, when, and how often — respecting contact rules and timing each attempt for the best chance of an answer.
Built in, then handed over.
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We sat inside the recovery operation — listened to real calls, mapped each delinquency bucket, and learned what actually moved an account toward paying.
Build
We built the stack under their brand — agents, adaptive scripts, AMD, QA scoring, retry logic, telephony — and tuned it against live calls before scaling.
Scale
By week two the agent was outperforming the human team. Over six weeks it took over the full book and replaced the forty-person dialing operation.
Transfer
Numbers, agents, data, and models went into their name. They pay carriers directly — no per-minute fees to us or anyone else.
A floor of forty, replaced in six weeks.
The agent contacted three times more debtors than the human teams it replaced — AMD filtering and timed calling windows meant nearly every minute went to a live conversation instead of a voicemail. Consistency stopped depending on who was on shift. Every call was scored, so quality became something the team could see and steer.
When it was done, the whole stack moved into the client's name — numbers, agents, data, models. This is the engagement model behind our Voice AI Infrastructure service: we build it under your brand, run it until it works, then hand you the keys. You pay carriers directly. No per-minute fees to us, or to anyone.
"We replaced 40 human collectors in six weeks. By week two the agent was already outperforming them."
Own your collections stack, don't rent it.
A 30-minute call. We'll map your buckets, your call volume, and what a voice stack you actually own would look like on your book — the engagement model behind our Voice AI Infrastructure service.