MayaAI in Practice: 4-Week Trial Results from a Sydney Specialist Clinic

This is a 4-week trial report. Figures updated 6 August 2026. Trial period: 7 July – 6 August 2026, at a Sydney-based specialist practice.

We deployed Maya, our AI voice receptionist, on the live phone line of a Sydney specialist practice. Over four weeks of live running, Maya answered real patient calls around the clock — booking appointments, rescheduling and cancelling them, taking messages, and connecting callers to the front desk when needed.

The single clearest finding: the majority of the patient calls Maya answered came outside normal clinic hours — calls that, without her, would most likely have reached a voicemail or gone unanswered.

This report covers genuine patient calls only. Internal test calls made during setup have been excluded so the figures reflect real-world use.

The headline numbers (4 weeks)

  • Genuine patient calls answered: 142
  • Total time Maya spent on the phone with patients: approx. 6.5 hours (391 minutes)
  • Average call length: approx. 2.8 minutes
  • Active days with patient calls: 25 of 31 days
  • Average per active day: approx. 15.6 minutes
  • Average per calendar day: approx. 12.6 minutes
  • Missed / unanswered patient calls: 0

    • Every genuine patient call that reached the line was answered. None went to voicemail.

    The after-hours story

    Traditional reception can only answer during opening hours. Maya answers every hour of every day — and the trial shows how much that matters.

    In the first three weeks of the four-week period, nearly six in ten patient calls Maya handled (59%) came outside standard clinic hours (Monday–Friday, 8:30am – 5:00pm), including calls on weekends and late in the evening.

    Before Maya, those calls would typically have reached a voicemail — which many callers hang up on rather than use — or gone unanswered entirely: a lost booking, a frustrated patient, and often a call that never comes back.

    Instead, patients calling after hours were able to book, reschedule, cancel, or leave a message, and get the same standard of experience as if a receptionist had picked up mid-morning.

    In practical terms: more than half of the value Maya delivered in this trial happened at times when a human receptionist simply would not have been at the desk.

    Growing use, week on week

    As the practice and its patients grew comfortable with Maya, call volume climbed. In the first three weeks of the trial, Maya answered 67 genuine patient calls (7 in a partial first week, 28 in week 2, and 32 in week 3). The trial then continued for another 9 days through to 6 August, adding 60 more patient calls. By the end of the 31-day period, Maya had answered 142 calls in total — all without adding a single minute of human reception time.

    What Maya actually did on the calls

    Beyond answering, Maya carried out the full range of front-desk tasks herself. Across the trial she demonstrated, on real calls:

  • Booking appointments: new-patient and follow-up appointments across the practice's multiple clinic locations, taking the patient's details and confirming the booking directly into the practice management system.
  • Rescheduling and cancelling: existing appointments.
  • Booking online (video) and phone consultations: , with the video link issued to the patient automatically.
  • Taking messages: for billing queries, "running late" notices, and callback requests, capturing the caller's details and reason and passing them to the team.
  • Connecting callers to the front desk: when a request genuinely needed a person.
  • Handling out-of-hours calls gracefully: , explaining when reception was closed and completing whatever could be done there and then, rather than leaving the caller with a dead end.

    • Maya was designed to *resolve* calls rather than simply pass them on — handling the request herself wherever possible, and reserving a transfer or message for when it was genuinely the right outcome.

    Why it matters for a practice

    For a specialist clinic, every missed call can be a missed appointment — and, for the patient, a missed opportunity to get care. This 4-week trial points to three concrete gains:

  • No missed calls: every genuine patient call was answered, including the 59% that arrived outside clinic hours.
  • Reception capacity reclaimed: more than six hours (6.5 hours) of live patient conversation were handled by Maya over the trial, without human reception time — and that share grows as call volume grows.
  • A consistent patient experience, any hour: callers received the same calm, capable handling at 9pm on a weekend as at 11am on a weekday.

    • About the trial

    Maya was deployed on the live inbound line of a Sydney-based specialist practice and integrated directly with the practice's management system for real-time booking. The figures in this report are drawn from Maya's own call records over the four-week trial period (7 July – 6 August 2026) and reflect genuine patient calls only; calls made internally for testing and configuration during setup have been excluded.

    The trial is ongoing, and we expect to publish extended results — including detailed booking, reschedule and cancellation counts — as call volume builds.

    About MayaAI

    MayaAI is an AI voice receptionist built specifically for Australian healthcare practices. Maya answers calls day and night, books, reschedules and cancels appointments, sends reminders and recalls, takes messages, and escalates urgent calls — integrating directly with the tools practices already use.

    Interested in a demonstration? Book a free 30-minute demo · human@mayaai.com.au

    *All figures are drawn from MayaAI's call analytics for the trial period (7 July – 6 August 2026). No patient-identifying information is included in this report. The participating practice is not named pending consent.*

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