Clinic OS: appointment
Appointment, records and follow-up system for a multi-doctor clinic, with an AI intake assistant that turns a patient's description into a structured pre-visit summary.
sample entry — replace with real work before launch (this page is set to noindex)
- ~70%
- less manual data entry
- 3 wks
- to first live doctor
- 24/7
- automated follow-up
Key features
- Multi-doctor calendar with slot rules and room allocation
- Patient records, prescriptions and visit history
- WhatsApp reminders and automated follow-up sequences
- Role-based access for doctors, reception and admin
- Reports on load, no-shows and revenue per service
UI/UX approach
Reception works at speed under pressure, so the calendar is the home screen and every frequent action is one click away. Type is large, contrast is high, destructive actions always confirm. The AI summary sits beside the doctor's notes as a suggestion panel, never as the record itself.
AI features
- Intake assistant converts free-text symptoms into a structured summary
- Prescription notes drafted from dictation, always doctor-approved
- No-show risk score used to overbook selected slots safely
- Semantic search across past visit notes
How AI changed the build
Requirements were drafted from raw interview transcripts in hours rather than days. Component scaffolding and CRUD layers were generated from the schema, and test cases from acceptance criteria — moving most of the build time to the parts needing judgement.
AI tools used
Technologies
Live link
Private build — walkthrough available on request.
How the project ran.
- Two days shadowing reception and consultation to map the real flow
- Clickable prototype tested with staff before any code
- Core booking and records built first, shipped to one doctor
- AI intake added behind a flag, evaluated on 200 past cases
- Rolled out clinic-wide with a week of on-site support
This follows the six-stage process every project uses.
Other project records.
Building something like Clinic OS?
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