Use cases
Voice AI agents for business on phone and WhatsApp.
Your team returns calls in hours. A voice agent answers on the first ring, speaks naturally, and finishes the task: a screening interview, an intake, a booking, a support request. We build voice agents for phone and WhatsApp with the two things demos skip: latency engineered to conversation speed, and a clean handoff to a human when the call leaves the script.
What are voice AI agents for business?
A voice AI agent is software that holds a real conversation on a phone line or WhatsApp and completes the work: a structured interview, an intake, a booking, a support request. Production agents differ from demos in two ways. Latency is engineered so replies land at conversation speed, because a long pause reads as a dead line. And escalation is designed in from day one: the agent hands the caller to a human, with transcript and context attached, the moment the conversation moves beyond its scope.
Who this is for
Companies where the phone still carries the business: hiring teams screening high volumes of candidates, clinics and insurers running intake, service operations juggling appointments, support lines answering the same questions all day. Our clients are funded startups and $10M to $100M companies with real call volume and no appetite for callers stuck on hold. If calls are rare and each one is a delicate negotiation, a voice agent is the wrong tool, and we will say so.
- Hiring platforms and recruiters running structured screening interviews
- Clinics, insurers and lenders collecting intake over the phone
- Service businesses booking, confirming and rescheduling appointments
- Support teams with a predictable question mix and after-hours gaps
- Businesses in WhatsApp-first markets where customers expect voice notes
How the system works
A production voice agent is a pipeline: speech comes in, the model reasons, speech goes out, and every step is streamed so the caller never waits on silence. We set a latency budget for each conversational turn and engineer the whole path against it, a discipline we learned building FRIDAI, a voice assistant for gamers, where a slow answer meant the player simply stopped using it. Callers behave the same way. The other half is escalation: the agent knows the edge of its scope, and crossing it triggers a warm handoff to a human with the full transcript and a structured summary. The same pipeline serves phone calls and WhatsApp, voice notes and text, from one logic layer.
- A latency budget per turn, engineered end to end, not hoped for
- Interruption handling: the caller can talk over the agent, and it stops and listens
- Structured call flows with model judgment inside each step
- Warm handoff to humans with transcript and context attached
- Approval gates before anything irreversible: bookings, payments, commitments
- Least-privilege access, audit logs and PII masking, designed to support DPDP, GDPR, HIPAA and SOC 2 expectations
The first workflow to automate
Start with one bounded, high-volume call type that has a clear beginning and end. Structured screening interviews, intake and appointment scheduling all qualify: the agent has a defined flow to hold, a clear definition of done, and an obvious moment to hand off. Open-ended support lines come later, after the agent has earned trust on the bounded work. The entry point is deliberately small: a scoped Agent Readiness Audit maps your call flow and gives you an honest go or no-go, or a scoped Prototype Sprint puts a working voice agent on your real call cases. Both begin with a founder-led 30-minute call.
- Screening interviews: fixed structure, clear rubric, human review of edge cases
- Intake: collect, validate and write to your systems in one call
- Scheduling: book, confirm and reschedule against a live calendar
- Support triage: resolve the routine, route the rest with context
How to measure success
We baseline before we build and instrument from day one, so the return is a report, not a claim. The numbers that matter for a voice agent are few, and they live on a dashboard you can check any morning.
- Containment rate: calls completed end to end without a human
- Turn latency: how long the caller waits for each reply
- Completion rate: callers who finish the interview, intake or booking
- Escalation quality: handoffs that arrive with context a human can act on
- Data accuracy: captured answers checked against sampled human review
- Cost per completed call, tracked next to what human handling costs
Proof from production
We built FRIDAI, a voice assistant for gamers that turns speech into in-game action, where low latency was the product: gamers abandon anything slow, and callers do the same. Under NDA, we run a voice AI interviewer for a hiring platform, conducting structured screening interviews end to end with humans reviewing the edge cases. Also under NDA: a WhatsApp digital therapist that holds sensitive conversations on the channel people already use. And Facebot, a conversational AI persona customers actually talk to. Different industries, one pattern: the conversation is the interface, and the engineering behind it decides whether people stay on the line. Built for teams worldwide since 2019.
How fast does a voice agent respond?
Fast enough that the conversation feels normal, or callers hang up. We set an explicit latency budget for each conversational turn and engineer the whole pipeline against it: streamed transcription, model routing chosen for speed, streamed speech out. This is the discipline we learned building FRIDAI for gamers, who abandon anything slow, and it carries directly to phone and WhatsApp.
What happens when a caller goes off script?
The agent recognizes the edge of its scope and hands off instead of improvising. A human gets the live call or a callback task, with the transcript and a structured summary attached, so the caller never repeats themselves. Anything irreversible, a booking, a payment, a commitment, sits behind an approval gate. Escalation is designed first, not bolted on after the first bad call.
Do voice agents work on WhatsApp?
Yes. The same agent that answers a phone line can hold a conversation over WhatsApp voice notes and text, which is where many customers already are. Under NDA, we operate a WhatsApp-native digital therapist, so we have production experience with sensitive conversations on that channel. One agent, one logic layer, multiple channels.
Is this safe for regulated industries like healthcare or finance?
It is designed for them. Voice agents get least-privilege access to your systems, every action is logged, personal data is masked before models see it, and data residency is honored. Human approval gates sit in front of high-stakes steps. The whole design is built to support DPDP, GDPR, HIPAA and SOC 2 expectations, and we structure it with your compliance obligations in the room.
What does a voice agent cost to run?
Running cost is dominated by model, speech and telephony usage, and it scales with call volume. We instrument cost per completed call from day one, next to what human handling of the same call costs, so the comparison is a number on a dashboard, not a hope. Setup is a fixed, scoped engagement.
How long until a voice agent is taking real calls?
Fast. A scoped Agent Readiness Audit maps one call flow and gives you a build plan with an honest go or no-go. A scoped Prototype Sprint puts a working voice agent on your real call cases, with the eval numbers attached. Production hardening follows from there, and it starts with a founder-led 30-minute call.
Talk to the people who build.
One call. An honest read on what AI can do for this, and the number it has to beat.