Voice AI
Front-desk voice agents that handle scheduling and support 24/7.
Voice AI that doesn't drop calls or get stuck in loops. We build front-desk agents that handle appointment scheduling, rescheduling, and customer support around the clock, plus domain-tuned transcription for clinical and back-office workflows.
Who Voice AI Is For
- Operations teams whose front desk is the bottleneck: scheduling, intake, after-hours coverage.
- Clinical and back-office teams whose transcription needs vocabulary the generic models don't know.
- Companies whose previous voice deployment failed because of latency, drops, or hand-off gaps.
How Voice AI Works
- Step 01
Workflow and integration map
Walk through the actual call flow with the operators who run it today, map the systems the agent has to touch, and decide where humans stay in the loop.
- Step 02
Voice stack build
Realtime transcription, intent and slot handling, scheduling and CRM integrations, hand-off to a human when confidence drops.
- Step 03
Latency and reliability work
Tune turn-taking, partial response handling, and fallback behavior so the call feels like a call, not a chatbot read aloud.
- Step 04
Domain tuning
Clinical or back-office vocabulary, accent robustness, and structured note output tuned to whatever the workflow needs the transcript to do downstream.
What you get
- Production voice agent integrated with scheduling and CRM systems.
- Domain-tuned transcription with structured output for downstream workflows.
- Hand-off and escalation paths with full call transcripts and agent rationale.
- Latency and reliability dashboards covering turn time, drops, and escalation rate.
Where we've shipped this
All case studies →AI Scribe & Telehealth Platform
Healthcare Startup · AI Scribe & Telehealth
Built an AI scribe, voice agents for patient intake, and a HIPAA-compliant telehealth platform from the ground up.
- V1 shipped in 4 weeks (web, iOS, iPadOS)
- 500+ consultations/month
Enterprise Voice & Speech Platform
AI Wearable Startup · B2C -> B2B Pivot
Transformed a B2C personal AI assistant into an enterprise-grade voice and speech platform for field sales.
- Successful B2C -> B2B pivot
- 3 enterprise clients onboarded
Frequently asked questions
What's the realistic accuracy of a voice agent for clinical scheduling?
For domain-tuned models on a constrained workflow like appointment booking, transcript accuracy in the high 90s is normal once vocabulary, accents, and call quality are handled. Task-completion rate, which is the metric that actually matters, depends on how the agent handles edge cases and handoffs. We measure both and tune against real call recordings, not synthetic benchmarks.
How do you handle handoffs to a human?
The agent is told upfront which situations require a handoff: low confidence, sensitive content, explicit user request, or any scenario flagged in the runbook. When a handoff fires, the call routes to the right human queue with full context attached, including the transcript, what the agent already tried, and why it stopped.
Does voice AI work in noisy environments or with strong accents?
Yes, with caveats. Noise suppression and accent-tolerant ASR are now table-stakes, but the quality you get out of the box varies by provider. We test against your actual call audio early and tune the stack: ASR choice, noise model, prompt phrasing, and confirmation patterns. A demo on clean audio is not the test that matters.
What's the typical timeline to a live voice agent?
4 to 6 weeks to a production-grade agent handling a single workflow end to end is typical. The first 1 to 2 weeks are spent on call-flow design, persona, and integration with your booking or CRM system. The rest is build, eval, and tuning against real call recordings before going live.
Let's build something that actually works.
Tell us where you are and what you need. We'll come back with a clear, honest plan within 48 hours.