All case studies

Dental

Pilot · target, not verified outcome

The source story marks its pilot metrics and customer quote as placeholders pending retrospective sign-off. Timing figures below are targets, not confirmed results.

Dental Practice Pilot — Front-Desk Bottleneck to Five-Minute New-Patient Acknowledgment

At a glance

  • Practice: <placeholder practice name> — independent dental practice, US-based.
  • Size: <placeholder> operatories per location, <placeholder> hygienists on staff.
  • Inbound volume: <placeholder> new-patient inquiries per month across web forms, missed-call, Google Business Profile messages, and email.
  • Pilot window: <placeholder start date> → <placeholder end date>.
  • Stack: TaskMind AI + their existing PMS + their existing calendar.

The front-desk bottleneck

  • Slow callbacks on new-patient web submissions — every minute past the five-minute mark is an appointment a competitor practice has a better shot at booking.
  • After-hours form fills sit untouched until the next morning — a prospective patient lands at 8:52 PM and a front-desk operator sees it at 9:20 AM.
  • After-hours auto-responses are generic, so the prospective patient's reply is generic ("call us back") and intake never happens.
  • Front-desk starts every day with a callback backlog they cannot fully clear before the next inbound wave lands.

What TaskMind AI automated

  1. Five-minute new-patient workflow. Every inbound web form, missed-call, Google Business Profile message, and email is routed through AI extract → operator/hygienist assignment → acknowledgment → PMS upsert → calendar slot → five-minute escalation if no front-desk lead takes it. 1
  2. Chair triage. After-hours inbound is auto-classified by line of care (general, hygiene, cosmetic, emergency, ortho) and queued to the right operatory's morning list instead of dumped in a shared inbox. 2
  3. Lapsed-patient reactivation. Patients overdue for a cleaning or recall receive a personalized outreach sequence that books straight into the chair calendar. 3

Front-desk time reclaimed

  • Hours per week reclaimed by the front-desk and hygiene coordinators: <placeholder>.
  • New-patient inquiries pre-qualified by AI before a human touches them: <placeholder>.
  • After-hours inquiries that received a five-minute acknowledgment instead of waiting until morning: <placeholder>.

Before / After

Swipe horizontally to compare the columns.
Pilot measures and targets
MetricBefore TaskMind (baseline)After TaskMind (pilot)
Median first-touch time on inbound new-patient inquiry<placeholder><placeholder> (target: under five minutes)
After-hours inquiries reached a human same business day<placeholder><placeholder>
New-patient inquiries front-desk had to manually triage per day<placeholder><placeholder>
Lapsed patients reactivated into a booked cleaning per month<placeholder><placeholder>

What the practice said

Insert one direct quote from the practice owner or office manager here — keep it short, specific, and anchored on front-desk relief or new-patient booking. Quote goes here once the pilot retrospective is signed off.

What to read next

Ready to discuss the workflow?

If your dental practice is working through a similar new-patient inquiry and front-desk response workflow, book a dental workflow demo to discuss how the process could fit your team.

Footnotes

  1. Five-minute template and escalation chain in src/lib/cron/seed-five-minute.ts and /api/workflows. ↩

  2. Chair domain model and per-line-of-care routing in src/lib/business/chair/. ↩

  3. Recall and reactivation outreach in src/lib/business/recall/. ↩