When an AI Receptionist reaches a situation that needs human judgment, the call can follow a configured transfer or forwarding path to staff. When a live handoff is not the right next step, the workflow can capture an appropriate callback or follow-up request.
The goal is not unrestricted autonomy. The AI Receptionist handles supported routine work while keeping relevant activity visible to the office.
How the call workflow works
A supported call may move through these stages:
- The AI Receptionist answers the incoming call.
- Available caller and business context is checked safely when it can be matched.
- Approved Business Knowledge guides supported answers.
- Appointment requests or other supported next steps are handled when appropriate.
- Relevant activity is recorded for the office.
- The call is transferred, forwarded, or given a follow-up path when human help is needed.
Not every call follows every step. A caller may not be recognized, an appointment may not be requested, and a transfer may not be necessary.
What if Luntive does not know the answer?
The AI Receptionist should use the approved information available to it rather than inventing an answer. If the information cannot be verified, the configured workflow can guide the caller toward staff help or a follow-up request.
This boundary matters. A useful receptionist is not one that claims to know everything; it is one that makes the next appropriate step clear.
What stays visible to the team?
Call activity, supported appointment actions, caller details, and follow-up information can remain connected to the office context where the workflow supports them. Staff can then understand what happened and step in without reconstructing the conversation from scratch.
Learn more about human control in the FAQ, review the setup journey in Getting Started, or request a demo to discuss your workflow.