58% of appointment bookings now happen outside opening hours, and £3,400 a month of missed-call revenue is back on the books for a Birmingham dental practice group.
Cavendish Dental Care, a three-site dental practice group in Birmingham, engaged ajairu to build a conversational AI assistant that handles appointment bookings and patient FAQs across the website and phone. Within 4 months, 58% of bookings were self-served outside practice hours, missed-call revenue recovered reached £3,400 per month, and 25 receptionist hours a week were redirected to patients in the chair. The fixed-price engagement paid for itself in 5 months.
Cavendish Dental Care Ltd is a dental practice group operating three surgeries across south Birmingham: Moseley, Kings Heath, and Solihull. The group, led by Principal Dentist and Clinical Director Dr. Amrit Kaur Bhachu, offers NHS and private dentistry to around 18,000 registered patients. Each site runs a small front-desk team of two or three receptionists who juggle in-person patients, a constantly ringing phone, and an online booking form that only worked for checkups, not for the treatments that actually generated revenue.
Dental patients book when dental pain arrives, and dental pain does not respect practice hours. Practice manager Daniel Osei had the call logs to prove the problem: a fifth of calls went unanswered during the lunchtime rush, and the after-hours answerphone filled up every evening with people who wanted an appointment, not a message. By the next morning many had already booked with another practice.
The key challenges were:
Cavendish Dental engaged ajairu's conversational AI service, a fixed-price engagement starting from £8,000. ajairu built a single conversational assistant that works across the group's website chat widget and its phone line, connected directly to the practice management system's diary.
The system was delivered in three phases:
Clinical safety rules were agreed with Dr. Bhachu before go-live: the assistant never gives clinical advice beyond published emergency guidance, always identifies itself as AI, and escalates anything urgent to the on-call dentist. Receptionists can view and override any booking the assistant makes. If you are weighing up this kind of investment, our guide on the ROI of AI for small businesses shows how to build the business case.
Four months after go-live, 58% of all appointment bookings were being made by patients themselves outside practice hours, between 7pm and 10pm on weekdays and across Sunday afternoons. These are slots that previously required a phone call the next morning, and a meaningful share of them are emergency and urgent appointments that would once have been lost to whichever competitor answered first.
The recovered revenue is the number Daniel watches closest. Call-log analysis before and after shows the assistant books or converts enquiries worth around £3,400 a month that would previously have been missed: after-hours checkups, emergency visits, and high-value private consultations routed to treatment coordinators with a qualified enquiry attached. That is roughly £41,000 a year returned to the group without a single extra staff hour.
Receptionists got their 25 hours a week back and immediately felt it. Instead of repeating answers from a laminated sheet, they help nervous patients in the waiting room, chase treatment plans, and keep the day running on time. Front-desk turnover, which had been a running sore, stopped being a problem within a quarter.
Against the fixed implementation fee, recovered revenue passed total cost during month 5, giving a payback period of five months. Everything after that is margin, and the assistant keeps improving as more conversations teach it the questions Moseley patients actually ask.
Patients book at 10pm while our receptionists are at home. Two thirds of bookings now happen without anyone lifting a phone, we recovered three and a half thousand pounds a month in missed-call revenue, and the system paid for itself in five months.
This engagement used one of our core services:
The assistant was built around the diary, not around a chatbot script. Because it books real appointments into the real schedule, every conversation ends in something concrete, and patients learned quickly that the website is now the fastest way to get seen, not a dead-end form in front of a phone queue.
Channel coverage mattered just as much. Dental demand is unpredictable and out of hours by nature, so an assistant that only worked during opening hours would have solved the smaller half of the problem. Covering web and phone, day and night, is what turned missed calls into recovered revenue rather than polite apologies.
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