Service
AI Voice Calling at Scale
Production AI voice systems that handle 50,000+ calls a week.
Facts at a glance
- Calls handled per week
- 50,000+
- Client tenants on current platform
- 20+
- Typical time to first production call
- 2–4 weeks
- Core stack
- VAPI · Twilio · Supabase · n8n
AI voice calling looks simple on a demo and gets brutal at scale. Once a deployment crosses a few thousand calls per day, the hard problems move from prompt design to infrastructure — queue management, concurrency limits, failover, rate-limiting, tenant isolation, and real-time observability. o1 Innovate builds and operates voice systems for both inbound and outbound use cases, currently handling 50,000+ calls per week across 20+ client tenants on a shared platform architecture.
What we build
Inbound voice: AI agents that answer calls, qualify callers, route to humans when needed, and write structured notes back to your CRM. Typical use cases are front-desk triage, lead qualification, and appointment scheduling.
Outbound voice: AI agents that run dialer campaigns for lead qualification, appointment reminders, and reactivation. Built with careful pacing, caller ID rotation, and compliance guardrails.
Multi-tenant infrastructure: one operational system serves many clients with full isolation — separate prompts, knowledge bases, CRMs, phone number pools, and reporting.
Stack
VAPI for the voice agent runtime. Twilio for telephony. Supabase as the data plane for tenant configuration, call logs, and transcripts. n8n for orchestration, webhooks, and CRM write-backs. Custom dashboards where standard tools don't fit.
Why this matters
Most AI voice projects fail at the handoff between demo and production — not at the AI layer, but at the boring operational work around it. We design for that from day one, which is why we can run 50K+ calls per week without our team growing linearly with call volume.
Frequently asked questions
- What's a realistic cost per call for AI voice at scale?
- Cost per call is dominated by telephony and model inference. For outbound campaigns with sub-3-minute calls on a commercial model, we typically see $0.08–$0.25 all-in per connected call. Inbound costs less per call but usage is less predictable.
- Can AI voice handle transfers to a human agent?
- Yes. Warm transfers with context briefing, cold transfers, callback scheduling, and escalation to human-only queues are all standard. The AI summarizes the call so the human doesn't have to re-qualify.
- What about compliance — TCPA, DNC, recording consent?
- Outbound voice at scale has to respect TCPA, state-level restrictions, and do-not-call lists. We build the compliance guardrails (time-of-day windows, DNC scrubbing, consent capture, jurisdiction-aware recording disclosure) into every outbound deployment.
- How long does a new client tenant take to stand up?
- On an existing platform, a new tenant with a new agent persona and knowledge base can go live in about a week. A new use case that requires new infrastructure (e.g., a new CRM integration or a compliance pattern we haven't built) takes longer.
- What happens when the voice model gets something wrong?
- We instrument every call — transcript, latency, sentiment, escalation triggers — and review a sample daily. Failures update the prompt, the knowledge base, or the routing logic. Over weeks this drives the error rate down; we treat voice agents as living systems, not one-time builds.