All-in-One AI Platform
Zentr connects LINE and website conversations with your booking calendar and customer history. Help customers find a time, confirm their visit and keep your team ready to welcome them.
The problem
When customers ask about your services, help them move from a question to an available time. Connect replies, scheduling and customer records so your team can pick up the conversation with context.
The chart below illustrates after-hours enquiries; it is not a measured customer result.
How it works
A Friday night at your shop — Zentr handles everything from the first message to the morning confirmation.
“Any nail slots free tomorrow afternoon?” — Zentr understands abbreviations, typos and the casual way people really type.
It reads every staff member’s schedule, subtracts booked slots, breaks and clean-up time between appointments, and offers only the times that actually work.
The customer picks 14:00 with May; the system locks the slot that second and creates a new customer profile in the CRM automatically.
It reconfirms in the morning with the shop location and a reschedule button, reducing forgotten appointments and no-shows.
Open the app for the first time that day: bookings are in order, no backlog of messages, nothing to catch up on.
Features
Most shops wire chat into a calendar, the calendar into a customer spreadsheet, then tally it all up by hand every month. Zentr connects all four so they work together from the start.
It knows your prices and promotions and which staff are best at what — and knows when to stop and hand off to a real person.
Split by staff, branch and service type, with prep time counted between appointments — so slots never clash in the first place.
Every time a customer messages or visits, the system links the history for you — no need to ask what colour they had last time.
Every Monday morning it sums up what happened last week and what to act on first this week.
What changes
Who it’s for
If your revenue is tied to your team’s appointment calendar, every empty slot is income that never comes back. Zentr is built specifically for this kind of business.
Nail & beauty salons
Aesthetic clinics
Spas & massage
Dental clinicsZentr Dental Edition
Badminton · pickleball & sports courtsZentr Sport Edition
Yoga & fitness studios
Photographers
Animal hospitals
Tattoo studios
Car service centres
Don’t see your business? Talk with our team — if your revenue depends on an appointment calendar, Zentr can adapt to your shop.
Start today
Use the trial to explore customer conversations, scheduling and follow-up in your daily work. See how the platform fits your team before choosing a package.
Prepare your service list, opening hours and staff schedules. Our team can help you plan setup.
Questions
You can choose either way — have it introduce itself as an automated assistant, or use your shop’s name and tone. Either way, when a customer asks something out of scope, Zentr hands off to a real admin with a conversation summary right away.
Have your service list, prices, opening hours and staff schedules ready. Setup time depends on your channels and data; contact our team to plan the steps for your business.
Every booking the AI makes appears on the admin screen with the source conversation, and you can edit or cancel it any time. You can also set rules for which jobs always need human confirmation first, such as high-value work or new customers.
Yes. We import bookings and customer lists from Excel, Google Calendar or the booking system you use now. During the trial, our team helps with the first migration at no charge.
Data is stored on servers in Thailand, encrypted both in transit and at rest. Access is role-based, and we support PDPA requirements including deletion at the data owner’s request.
Explore booking, CRM and AI Insights during your one-month trial. Ask our team to confirm the trial allowances for your channels and staff, and review the pricing page before choosing a paid package.
Start with your next customer
Start with your service list and schedule. Try the booking journey with your team, then choose the package that fits.
