Carepulse

nurse dashboard
Patient health AI(diagnose)
Patient appointment page
medicine information page in pateint app
Doctor timeslot configuration for patient booking
patients vital entry in nurse portal
superadmin dashboard
Hospital Admin dashboard
Hospital Receptionist pateint checkin page
Doctor dashboard
Patient home page
pateint consulting page in doctor portal
Hospital Receptionist dashboard
prescription history page in patient portal
pateint consulting page in doctor portal
offline booking for patient

Inspiration

Visiting a hospital in India often means arriving early, standing in a queue, and not knowing which doctor to see or when you'll be called. We wanted to fix both problems: getting the right care and getting it without the wait. That became CarePulse, a hospital appointment and patient guidance system built on one idea: smarter care, shorter waits.

What it does

CarePulse is a patient-facing mobile app backed by role-based staff portals.

Patient app

Sign in with credentials, Google One-Tap, or biometrics Home dashboard with appointment tickets, specialties, notifications, and medicine reminders AI Health Triage Assistant that suggests the right specialty, shows a confidence score, and escalates urgent symptoms GPS-based search for nearby hospitals and clinics Doctor profiles with booking that generates a ticket code (e.g. #CP-4821) EMR vault for SOAP notes, prescriptions, and reminders

Staff portals

Superadmin adds a hospital and creates its admin login Hospital admin creates doctor and receptionist accounts and sees a dashboard of hospitals, desks, bookings, patients, and volume trends Receptionist manages doctor time slots and token counts, and views patient bookings Doctor portal for schedules and patients A unified staff login that routes each person to the right portal for their hospital How we built it Frontend: React Native for the patient app and React + TypeScript for the staff portals, with UI concepts generated in Google Stitch and refined by hand Backend and database: [add your stack here] AI: a triage model that maps symptoms to a specialty and returns a confidence score Booking logic: every time slot has a fixed number of tokens, so availability is $$\text{available tokens} = N_{\text{slot}} - B_{\text{slot}}$$

where ( N_{\text{slot}} ) is the slot capacity and ( B_{\text{slot}} ) is the number already booked. When a receptionist updates a slot, the change shows up in the patient app.

The work was split three ways: Sivanagu E on frontend, Abinandhan K on backend and database, and Monish JB on AI.

Challenges we ran into Keeping everything in sync: a slot edited at the reception desk had to show up correctly in the patient app. Multi-hospital roles: superadmins, hospital admins, receptionists, and doctors each needed their own scope, and login had to open the right portal for the right hospital. Native Google Sign-In: we wanted a smooth in-app flow with no browser redirect, which took extra setup in React Native. Design consistency: making four portals and the patient app feel like one premium product, including redesigning the staff login until it looked distinct. Responsible AI triage: the assistant had to be helpful without overstepping, so we added confidence scores and urgent-case escalation instead of presenting guesses as diagnoses. Accomplishments that we're proud of A complete end-to-end flow: a hospital added by the superadmin appears in the patient app, and a patient can book a token that the receptionist sees right away An AI triage assistant that is transparent about its confidence and escalates urgent cases A consistent, premium look across the patient app and all staff portals A unified staff login with role-based routing for every hospital [Add any result you're proud of, such as a live demo, user feedback, or a hackathon milestone] What we learned Designing role-based access and data flow across several types of users Building booking that feels real-time without double-booking tokens Making AI output transparent and safe in a healthcare setting Keeping one design system consistent across web and mobile Working as a three-person team with clearly split frontend, backend, and AI ownership What's next for CarePulse Live queue tracking and wait-time estimates Multilingual support, including Tamil Teleconsultation Deeper EMR integration with real hospital systems Pilot testing with a local hospital or clinic