500,000 Calls a Month. Seven Languages.
The hard economics of AI calling at scale — from $0.30 to $0.12 per minute, with two case studies that prove it works.
See the EconomicsThe Real Cost of Human vs AI Calling
When you factor in all costs — salary, training, supervision, infrastructure — the math is clear.
- Agent salary + benefits
- Training & onboarding (3-6 weeks)
- Supervisor overhead
- QA & compliance monitoring
- Infrastructure & telephony
- Per-minute compute
- No training ramp-up
- Zero supervisor overhead
- Automated compliance
- Scales instantly
Outbound at Scale
An enterprise fintech needed to make 500,000+ outbound calls per month across seven languages — collections, payment reminders, product upsells. Their 200-person call center couldn't scale further without proportionally scaling costs.
We deployed AI voice agents that handle the initial conversation, qualify intent, and route to human agents only when needed. The AI handles scripted flows with natural conversation — not a robocall, but an actual dialogue that adapts to responses.
35% of calls are fully resolved by AI without human intervention. The remaining 65% are warm-transferred with full context, so the human agent picks up mid-conversation instead of starting from scratch.
The Audio Quality Problem
The first case study was about volume. The second is about quality. A late-stage B2C company had a different problem: their inbound and outbound calls had terrible audio quality. Background noise, echo, compression artifacts — all killing conversion rates.
Standard noise cancellation tools added 200-400ms of latency. Acceptable for a podcast recording. Unacceptable for a live sales call where every millisecond of delay makes the conversation feel unnatural.
They needed custom noise cancellation that runs in under 50ms — fast enough that neither party notices the processing.
Custom Voice Enhancement
A custom noise cancellation model trained on their specific audio environment — not a generic solution, but one tuned to their call center acoustics.
We trained a custom noise cancellation model on recordings from their actual call center — learning the specific acoustic profile, background noise patterns, and codec artifacts of their environment. The result: crystal clear audio at under 50ms latency, with a 15% lift in conversion rates from cleaner conversations.
Both Directions, One Platform
Outbound — Collections, payment reminders, product upsells, surveys, appointment confirmations. AI handles the scripted flows. Humans handle the exceptions.
Inbound — IVR replacement, first-call resolution for common issues, intelligent routing with context. Customers talk to AI that understands their account, not a menu tree.
Voice Enhancement — Custom noise cancellation and audio optimization that runs transparently on every call. Better audio means better comprehension means better outcomes.
The shared infrastructure means outbound and inbound AI share learnings — the system gets better at every call type as total volume increases.
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Have a challenge that needs AI? We'd love to hear about it.