AI front desk development
An AI front desk that gives inquiries a clear next step.
We build AI front desks that answer the questions you have approved, take down requests and book appointments where your calendar allows it. Before launch we agree the rules with you, connect your systems and test the handoffs to your staff.
The consultation is free and takes 30 minutes. We talk through your workflow and what a first version would cover.
Start with what happens after someone asks.
A fast reply only helps if the request then goes somewhere. An answer, a saved request and a confirmed appointment are three different results. The customer and your team both need to be able to tell which one they got.
Take an appointment request that comes in after hours. The assistant needs to know the service, how long it takes, who is available and your booking rules. If the calendar cannot confirm a slot, the assistant saves the request for staff to confirm, with a named owner and a way to follow up.
We map that path before we build anything: which questions the assistant may answer, which actions it may take, where the record is saved and who handles exceptions. That map is what we test the finished build against.
Answer from approved information
The assistant uses your current hours, services, locations and pricing rules. You decide who keeps that information up to date and what the assistant does when it has no answer.
Capture a request someone can act on
The request and the contact details you agreed to collect go into the system your team already uses. A transcript alone gives nobody the job of following up.
Confirm only what was saved
The assistant checks availability and permissions, submits the booking and reads the result that comes back. It tells the customer the appointment is confirmed once the connected system has saved it.
Example conversation
Tell the customer what was confirmed.
This written example shows one way an appointment request can go. It is not a live assistant or a real customer conversation, and it does not show that a calendar is connected.
The step to watch is the result of the save. If the provider times out or rejects the appointment, the assistant tells the customer that confirmation is pending and passes the request to staff. Before it retries a booking, it checks for a duplicate.
Customer: Can I book an appointment tomorrow?
Assistant: Which service do you need? I can check the available times.
Customer: A consultation at 10:30, if that is available.
What the system does here: it checks the service rules and availability, submits the appointment and gets back a booking reference.
Assistant, after a successful save: Your consultation is confirmed for 10:30 tomorrow. Here is your booking reference.
Example ends here. No real appointment has been created.
What we are responsible for.
A scope based on the systems you have. We look at your phone routing, messaging and calendar access, then say which channels and actions are included. If direct booking is not supported, a first release that only takes requests can still be useful.
Rules your staff can review. We agree with you the approved answers, operating hours, customer permissions and opt-outs, where handoffs go and who maintains the business information. We also agree where the assistant stops on sensitive or unsupported requests.
Checks before launch. We test routine questions, unavailable slots, changed appointments, provider failures, duplicate requests and escalation to staff. We agree with you what counts as a successful save and what stays pending.
A handover you can use. You get operating instructions, a record of who is responsible for each account and a way to see failures. The proposal lists implementation, provider charges and ongoing support separately, and the timing depends on scope and access.
For an example of our voice agent work, read the UpGig case study and its candidate phone-screening workflow. Your front desk will have its own integration scope and its own checks.
Common questions.
Can an AI front desk work with my existing phone and calendar?
It depends on your providers and the access they allow. We check call routing, messaging, calendar permissions and booking rules before we propose an integration. Where a direct connection is not available, the assistant can record the request and hand it to staff. It does not tell the customer an appointment is booked.
What happens when it cannot answer a question?
We set that limit with you before launch. The assistant answers from approved business information, asks a clarifying question when that would help, and sends anything it does not support to a named person or queue. The handoff carries the customer request and contact details, and it has an owner who follows up.
Will this guarantee more bookings or fewer no-shows?
No. Answering more inquiries, sending reminders and following up can all help the booking process, but the results depend on demand, availability, your offer and how customers behave. We agree with you what to measure, such as requests captured, confirmed appointments, failed saves and unresolved handoffs, and then look at the real numbers.
What will TDAT deliver, and what will it cost?
The proposal sets out the supported channels, integrations, approved answers, booking permissions, human handoffs, acceptance checks and who is responsible for what after launch. We agree the implementation price, provider charges, support and launch timing after we have reviewed your current workflow and access. The free consultation is where we talk through that scope.
We can build the workflow and test it.
Bring the inquiry or booking process you want to hand over. On a free 30-minute consultation we go through the systems you use now, the result you need and what a first version should cover.
Book a free consultation