Case studyTelemedicine11 min read

Nabz Care: a telemedicine platform built for villages with one bar of signal

A health startup wanted to connect villages to qualified doctors through trained community health workers. Every mainstream telemedicine app assumed good video and a patient with a smartphone. We built Nabz Care: a health-worker app that works offline, audio-first consultations that degrade gracefully, device-connected vitals and e-prescriptions to local pharmacies — 26 features designed for the network that actually exists.

26
Features shipped
4
Apps & platforms
10
Team members
24
Weeks to rollout
Nabz Care health-worker app and doctor console
Nabz Care: a village consultation, a remote doctor, a local pharmacy.
01

The pilot that failed first

Nabz Care's founders came to us after a pilot that did not work. They had used an off-the-shelf video consultation app in twenty villages. Calls dropped constantly, health workers spent more time reconnecting than consulting, and doctors could not see or hear enough to prescribe with confidence. Within a month the health workers had gone back to asking patients to travel to the district town.

The founders' model was sound: trained community health workers in each village, qualified doctors consulting remotely, medicines from a local pharmacy. What failed was software designed for city broadband.

“The doctors were ready. The health workers were ready. The app wasn't built for where they live.”

— Nabz Care's co-founder
02

Two weeks in the villages

Our designer and engagement lead spent two weeks with health workers across both states. We measured the network in each village at different times of day, watched consultations on the old app, and sat with patients who had never spoken to a doctor on a phone before.

The network was rarely absent but almost always weak: enough for audio most of the time, enough for video some of the time, and enough for small data syncs nearly always. Health workers were capable and motivated, but most were more comfortable in Hindi or the local dialect than in English, and their phones were entry-level Android devices shared with their families.

What the field told us
  • Audio works far more often than video
  • Data sync works almost everywhere if it can retry
  • Health workers need Hindi, large text and very few steps
  • Doctors need vitals and history before the call starts, not during it
Agricultural field under an open sky
Designing for the network that exists: weak, but rarely absent.
03

A consultation that degrades gracefully

The core idea of Nabz Care is that the consultation does not depend on the call. Before connecting, the health worker records symptoms (by voice, transcribed from Hindi), captures vitals from Bluetooth devices, and takes photos of any visible condition. That packet syncs to the doctor first — it is small and survives weak networks.

Only then does the call start. It begins as video if the network allows, drops automatically to audio if it does not, and falls back to an asynchronous consult — the doctor reviews the packet and responds with a prescription and advice — if even audio fails. The patient is never left without an outcome.

04

The team

Native Android was essential for reliable Bluetooth and offline behaviour, so the mobile team was the largest part of the project.

1
Engagement lead

Field research, pilot relaunch and expansion planning.

1
Product designer

Hindi-first health-worker app and doctor console.

3
Android engineers

Offline-first app, Bluetooth devices and adaptive calling.

1
Frontend engineer

Doctor console, pharmacy app and operations dashboard.

2
Backend engineers

Sync service, consultation workflow and e-prescriptions.

1
AI engineer

Hindi speech-to-text and symptom note structuring.

1
QA engineer

Network simulation, device testing and field testing.

10 people in total, working as one team.

05

Decisions that made it work

Each decision was tested in the field before being locked in.

01

Video-first or data-first consultations?

  • Video call as the core experience
  • Data packet first, then adaptive video, audio or asynchronous consult

Our call: Data packet first, then adaptive video, audio or asynchronous consult. Small data syncs survive weak networks; live video often does not. Sending vitals, notes and photos first meant every consultation could reach an outcome.

02

Cross-platform or native Android?

  • Cross-platform framework
  • Native Kotlin Android

Our call: Native Kotlin Android. Reliable Bluetooth device connections, background sync and fine control over calls on entry-level phones were easier and more robust natively. All health workers used Android.

03

How should health workers record symptoms?

  • Typed English forms
  • Hindi voice notes transcribed and structured

Our call: Hindi voice notes transcribed and structured. Typing in English was slow and error-prone for most health workers. Speaking in Hindi was natural; transcription and structuring made it useful to the doctor.

04

Should AI triage patients?

  • AI decides urgency
  • Rule-based danger signs flagged; doctors decide

Our call: Rule-based danger signs flagged; doctors decide. Clear danger-sign rules, agreed with the medical team, flag urgent cases reliably. Clinical judgement stays with the doctor.

06

The 26 features

Everything that shipped, for health workers, doctors, pharmacies and the operations team.

Health-worker app
Built for one bar of signal.
  • 01Offline patient registration

    Register patients and families without a connection.

  • 02Hindi voice symptom notes

    Speak symptoms; they are transcribed and structured.

  • 03Bluetooth vitals

    Blood pressure, SpO2, temperature and glucose from connected devices.

  • 04Photo capture

    Photos of visible conditions attached to the consult.

  • 05Danger-sign checklist

    Rule-based flags for urgent referral.

  • 06Background sync with retries

    Data syncs whenever any signal is available.

Consultation
Every consult reaches an outcome.
  • 07Adaptive calling

    Video, then audio, depending on the live network.

  • 08Asynchronous consults

    Doctor responds to the packet if a call is not possible.

  • 09Doctor queue by urgency

    Urgent cases surface first.

  • 10Consultation packet view

    Vitals, notes and photos before the call starts.

  • 11Referral workflow

    Referral letters to district hospitals with follow-up tracking.

Prescriptions and pharmacy
Medicine close to home.
  • 12E-prescriptions

    Structured prescriptions sent to the health worker and pharmacy.

  • 13Local pharmacy app

    Pharmacies receive prescriptions and confirm dispensing.

  • 14Printable prescription

    Hindi printout for patients via a small printer.

  • 15Medicine adherence reminders

    Voice call and SMS reminders for patients.

Patient records
Continuity of care.
  • 16Family health records

    Records organised by household.

  • 17Visit history

    Every consult, vital and prescription over time.

  • 18Chronic disease follow-ups

    Scheduled follow-ups for diabetes and hypertension.

  • 19Health ID linking

    Link records with the national digital health ID.

Operations
Running a hundred villages.
  • 20Operations dashboard

    Consultations, doctors online and health-worker activity.

  • 21Network quality map

    Connection quality per village over time.

  • 22Doctor rostering

    Doctor shifts and availability.

  • 23Health-worker performance

    Consultations, follow-ups and training status.

  • 24Role-based access and audit

    Controlled access to records with full logs.

  • 25Consent capture

    Patient consent recorded before every consult.

  • 26Device management

    Track and update health-worker phones and devices.

Nabz Care doctor console with consultation packet
The doctor console: the consultation packet arrives before the call does.
07

From twenty villages to a hundred

We relaunched in the same twenty villages where the original pilot had failed — deliberately. Health workers who had given up on the old app were the toughest possible test. Within weeks they were completing consultations that previously would have meant a trip to town.

Expansion to a hundred villages followed in waves, each with a two-day training for new health workers run partly by experienced ones from the first wave.

  1. Weeks 1–3
    Field research

    Two weeks in villages; networks measured, failed pilot analysed.

  2. Weeks 4–6
    Design

    Hindi-first prototypes tested with health workers in the field.

  3. Weeks 7–15
    Build

    Native app, sync service, adaptive calling and doctor console.

  4. Weeks 16–18
    Relaunch

    Same twenty villages as the failed pilot.

  5. Weeks 19–24
    Expansion

    A hundred villages in waves, with peer-led training.

08

What we learned

Design for the median connection, not the best one. Separating the data packet from the live call made the product work on the network villages actually have.

The health worker is the product's real user. Every feature that saved them a step or a language barrier improved care more than any feature for doctors.

Built with
  • Kotlin (Android)
  • Next.js
  • NestJS
  • PostgreSQL
  • WebRTC with audio fallback
  • Bluetooth medical devices
  • Hindi speech-to-text
  • AWS Mumbai
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