What is an AI receptionist agent?
An AI receptionist agent answers calls, routes callers, captures messages, and helps with scheduling. It acts like a front-desk layer that follows your business rules.
Front desk coverage
AI Receptionist Agent
Answer calls, route customers, book appointments, capture messages, and support the front desk after hours. Refract trains this agent on your workflow, approved knowledge, tools, and handoff rules so your team gets more coverage without losing control.
Who it helps
Built for the people already carrying this workflow.
Refract is designed to give teams more leverage, cleaner context, and more reliable follow-through. The agent handles the repeatable parts, while people stay involved where judgment matters.
- Receptionists
- Virtual assistants
- Front desk coordinators
- Phone operators
- Office administrators
Workflow
The work this agent can help move forward.
01
Answer inbound calls when staff are busy or offline
02
Route callers to the right person or department
03
Book, reschedule, or confirm appointments
04
Capture messages with complete caller context
05
Answer basic business questions from approved content
06
Send call summaries to email, CRM, or team chat
Sample scenario
See how it handles a real conversation.
A representative exchange — what the agent hears, what it asks, what it captures, and when it hands off to a person.
A caller reaches a dental practice at 6:50pm, 50 minutes after the office closed, looking to book a new patient appointment.
Caller
Hi, I'm trying to book an appointment. I think you close at 6?
Agent
The office is closed for the evening, but I can check availability and book you in right now if that works?
Caller
Oh great, yes please.
Agent
Are you a new patient or have you been here before?
Caller
New patient.
Agent
Got it. What's your name and a good callback number?
Caller
Marcus Webb, 111-111-1111.
Agent
Thanks Marcus. I have Tuesday at 9am or Wednesday at 11am open for new patient appointments. Which works better?
Caller
Tuesday at 9 works.
Agent
Booked. You'll get a confirmation text to 111-111-1111 shortly. If anything comes up, the office number is on that message.
Collected
- Caller name (Marcus Webb)
- Callback number (111-111-1111)
- New patient
- Appointment: Tuesday 9:00 AM (confirmed)
Action taken
Appointment booked directly via calendar integration. Confirmation text queued. New patient record created.
Outcome
Patient books the slot in real time. No callback needed the next morning, no risk of the slot filling overnight.
Handoff rule
Would transfer immediately if the caller described a dental emergency, acute pain, or asked a clinical question.
What improves
What gets better when this agent is running.
- Fewer missed calls
- Better after-hours coverage
- Cleaner caller messages
- Less front-desk interruption during busy periods
Connections
System categories it connects to.
Phone systemCalendarCRMEmailSlack or TeamsScheduling system
Specific integrations confirmed at scoping.
Controls
Guardrails that keep it useful.
- Business-hours rules
- Approved routing paths
- Appointment booking constraints
- Human transfer for sensitive or unusual calls
FAQ
Questions teams ask before they deploy.
How is this different from a virtual receptionist service?
A virtual receptionist service usually depends on outside staff. Refract gives you an agent trained on your scripts, routing rules, and systems, with human handoff when needed.
Can it schedule appointments?
Yes. Refract can follow your scheduling rules and connect to a calendar or booking workflow when the integration is available.
Can it transfer calls to the right person?
Yes. The agent can route calls by caller need, department, location, urgency, or account type.
Can it answer after-hours calls?
Yes. After-hours coverage is one of the clearest use cases. The agent can answer, collect context, route urgent needs, and send a summary to your team.
Start here
Map one workflow before you expand the agent.
Bring the process, examples, routing rules, and systems this service needs to use. We will help you decide what should be automated, what should be escalated, and how to prove the first deployment.
Talk through your AI Receptionist Agent
Share the workflow, current bottleneck, and tools involved. We will follow up with a practical first-deployment path.