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AI Engineering · Healthtech2026Backend & AI Engineer
02

Joy / Rehabify Health

AI-guided care access with safety outside the model

GeminiTypeScriptPostgresWhatsApp API

Overview

Joy is Rehabify Health’s WhatsApp-native care companion. Patients can describe what hurts in English, Yoruba, Igbo, or Hausa, move through intake and matching, book a verified physiotherapist, and continue recovery follow-up in a channel they already use.

01 / Challenge

The conditions that shaped the system.

A useful architecture begins with the real constraint.

The experience needed to feel as simple as a conversation while coordinating sensitive health context, clinical red flags, identity, permissions, therapist matching, bookings, and payments. Safety-critical behavior could not depend on a generative model alone.

02 / System map

From input to outcome

01Patient on WhatsApp
02Identity router
03Safety rules
04Gemini
05Care context
06Matching & booking
03 / Approach

How the build was organised.

Make the boundaries clear, then move.

  1. 01

    Separated deterministic clinical red-flag checks from generative responses so urgent conditions follow explicit rules.

  2. 02

    Built identity-aware routing and persistent context for conversations that continue across sessions and care stages.

  3. 03

    Connected therapist matching, booking, payment, and follow-up actions to the same WhatsApp-native journey.

04 / Engineering decisions

Decisions that carried the product.

01

Safety before generation

A deterministic safety layer evaluates critical signals before an AI response is composed.

02

Persistent context

Conversation state and patient context survive session boundaries so the assistant can continue coherently.

03

Channel-native workflow

Bookings and follow-up actions stay close to the WhatsApp experience patients already understand.

05 / Outcomes

What changed after the work.

Visit the live product ↗
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