Recall List Recovery

For

Practice managers at private dental and physiotherapy clinics

Solves

Overdue patient recall lists are long, full of dead numbers, and rarely get fully worked through, so clinics miss care and revenue.

Delivers

Booked appointments, daily staff summary, flagged conversation log

Built in

about 4 weeks of creation time, MVP in 5 days

Investment

$8,500 for the MVP, $32,500 for the full product

Run it

Inside your business, or as part of your offer to clients

For practice managers at private dental and physiotherapy clinics, turn the overdue recall list from the practice management system into booked appointments and a clean daily exception queue.

1. Pull overdue patients nightly from the practice management system.
2. Check contact history and suppression list before any outreach.
3. Choose channel by preference and bounce history.
4. Send personalised SMS, email or AI voice call with live slot offers.
5. Handle replies conversationally and propose two real slots.
6. Generate a daily summary for staff sign-off.

What goes in, what comes out

The workflow

1. In
   Start with

   Overdue recall list, patient contact preferences, live appointment calendar, suppression list

2. 1

   Pull overdue list

3. 2

   Filter suppression list

4. 3

   Select channel

5. 4

   Send personalised message

6. 5

   Handle replies with AI

7. 6

   Propose and book slots

8. 7

   Review daily summary

9. Out
   Finish with

   Booked appointments, daily staff summary, flagged conversation log

AI does the heavy lifting, people stay in charge

Use language models to draft plain-language messages and run a conversational voice or text agent that answers simple questions and proposes slots. A deterministic scheduler checks recall dates and suppression flags. A human receptionist reviews every booking and any flagged reply before it is committed.

What your team sees

Key screens: Recall dashboard, patient outreach queue, booking confirmation log. Use a dashboard showing overdue counts by type and channel, a queue of patients with contact preference and suppression flags, and a log of AI conversations and bookings. Let staff filter by appointment type and date. Display outreach status: sent, replied, booked, declined, flagged. Provide a single-click approval for AI-proposed bookings. In this product, the first view is recall dashboard, followed by patient outreach queue and booking confirmation log.

Accounts and administration

Clinic-level accounts, staff roles for review and sign-off, message templates, suppression list management, booking audit trail, opt-out records and a full conversation log for compliance.

Integrations and data access

Practice management systems such as Dentrix or Exact, SMS and email providers, and the clinic's live appointment calendar.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   5 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   10 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will practice managers at private dental and physiotherapy clinics use it to solve "overdue patient recall lists are long, full of dead numbers, and rarely get fully worked through, so clinics miss care and revenue"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. A four-week paid pilot at one clinic proves it by comparing the conversion rate of the AI-worked list against the prior quarter's manual recall conversion.
4. Measure, then decide. Track recall list conversion rate and number of bookings made without staff phone calls. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One dental clinic, one appointment type such as six-month check, SMS and email only, fixed slot set, and manual review of every booking before commit.

After the MVP. Add AI voice calls, multiple appointment types, automatic follow-up scheduling for declined patients, and direct booking into the live calendar without manual review for low-risk cases.

What the build depends on. A reliable API for the practice management system, a suppression list data source, and a compliant messaging setup with opt-out handling.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test at USD 300 per clinic per month, plus a small per-booking fee of USD 2, as a hypothesis.

Message to test

Turn your overdue recall list into booked appointments while your team sleeps.

Where to find buyers

Dental and physio practice manager forums, industry conferences, and direct outreach to clinic owners via LinkedIn and email.

Lead magnet

A free two-week trial on one appointment type, showing the conversion rate on your own recall list.

The first 30 days

1. Week 1: Connect to one practice management system and build the recall trigger.
2. Week 2: Build the suppression list and message templates.
3. Week 3: Run SMS and email outreach with manual booking review.
4. Week 4: Test with the pilot clinic and refine the daily summary.

Paid pilot

A four-week paid pilot at one clinic proves it by comparing the conversion rate of the AI-worked list against the prior quarter's manual recall conversion. The decision to continue is based on at least a 20% increase in booked recall appointments with no compliance incidents.

Success metrics

Recall list conversion rate and number of bookings made without staff phone calls.

Retention and expansion

The system keeps working nightly with no staff effort, and each month it learns better phrasing and timing, so the clinic sees compounding recall revenue and stays because the alternative is a guilt pile again.

Why clients would pick it

The more clinics use it, the better the AI gets at phrasing, timing and handling edge cases, and the suppression and compliance rules become a benchmark competitors cannot match without the same accumulated data.

Alternatives and positioning

Receptionists manually calling down a printed recall list on a quiet Friday. This differs by working the whole list overnight, across channels, and booking straight into the calendar.

Main delivery costs

Practice management system integration, AI conversation minutes, SMS and email sending, and support time for setup and troubleshooting.

Strict suppression list enforced before any contact, opt-out on every message, human review of all bookings and flagged replies, role-based permissions, and a rule that the AI must never contact a patient on a suppression list or make a booking without staff approval in the pilot phase.