AI Voice Agents
Phone-based AI agents that handle scheduling, intake, and routine calls without making callers feel like they're talking to a machine that doesn't listen.
What this is
We build voice agents for inbound and outbound calls — appointment scheduling, intake screening, order status, and call routing — using current speech-to-text and low-latency voice models, with a clear, tested handoff to a human for anything the agent shouldn't handle alone.
Who it's for
- Businesses with high call volume for scheduling or intake (clinics, home services, real estate)
- Teams missing calls after hours or during peak volume
- Companies wanting consistent intake screening before a human gets involved
The problem
Phone calls still convert better than forms for a lot of businesses, but staffing a phone line for every call — including after-hours and overflow — is expensive, and voicemail loses leads.
What it automates
- Inbound scheduling and rescheduling
- Intake screening (qualifying questions before a human call)
- Order/appointment status lookups
- After-hours call capture with structured callback requests
How it works
Call flow design
Map the actual call types you receive and design a script/decision tree for each, written the way your team actually talks.
Voice build
Configure speech recognition, voice model, and calendar/CRM integration; test extensively against real accents, background noise, and interruptions.
Escalation & fallback
Explicit rules for when to transfer to a human live, and a fallback path if the caller is frustrated or the agent is uncertain.
Launch & monitor
Phased rollout with call recordings reviewed weekly to catch misunderstandings early.
What it integrates with
What implementation involves
Discovery (1 week)
Call-type mapping, script drafting.
Build (2-4 weeks)
Voice configuration, calendar/CRM integration, escalation logic.
Testing
Structured test calls across accents and edge cases before go-live.
Launch
Phased rollout, weekly call-quality review.
Limitations — honestly
- Voice AI is honest work but not magic — heavy background noise, strong accents mixed with poor phone audio, or highly emotional calls still need a human fallback
- Regulated industries (e.g. medical, legal advice) require careful scoping of what the agent is allowed to say
- Ongoing call-quality review is recommended for the first month after launch
Realistic outcomes
- Captures calls that would otherwise go to voicemail
- Reduces staff time spent on routine scheduling calls
- Provides consistent intake screening before a human is looped in
Frequently asked questions
We don't build agents to deceive callers — most implementations disclose it's an automated assistant upfront, which callers generally accept for scheduling-type calls when the experience is fast and works. This also isn't just good practice: the FCC has ruled that AI-generated voices used in calls fall under the same TCPA consent and disclosure rules as other artificial voice calls (see: https://www.fcc.gov/document/fcc-makes-ai-generated-voices-robocalls-illegal).
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