Bloom - AI-Powered Maternal Health Platform

An AI-powered maternal health CRM platform designed for Nigerian mothers, connecting them with healthcare providers through intelligent health triage and voice-first interactions.

Live Demo: bloom-sigma-lake.vercel.app

Backend API: bloombbbb.azurewebsites.net

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The Problem

Nigeria has one of the highest maternal mortality rates globally - 512 deaths per 100,000 live births. Many complications are preventable with early detection, but mothers in underserved communities lack continuous access to healthcare guidance between clinic visits.

Key Challenges

• Limited access to healthcare professionals between appointments
• Low health literacy among expectant mothers
• Delayed recognition of warning signs
• Poor communication between mothers and healthcare facilities
• Lack of continuous monitoring during pregnancy

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Our Solution

Bloom bridges the gap between expecting mothers and healthcare facilities through an AI-powered platform that provides:

Feature	Description
AI Health Triage	Llama 3.3 70B Turbo analyzes symptoms in real-time, classifying urgency levels (critical/urgent/moderate/normal)
Voice-First Interface	OpenAI Whisper + TTS enables accessibility for mothers with limited literacy
Healthcare CRM	Hospitals connect with patients, view Life Passports, and receive AI-filtered health reports
Gamified Engagement	Token rewards for completing health check-ins and educational content
40-Week Education	Daily lessons tailored to each week of pregnancy

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Tech Stack

Frontend

Technology	Purpose
React 18	UI Framework
Vite	Build tool & dev server
Tailwind CSS v4	Styling (with @theme blocks)
React Router DOM	Client-side routing
React Query	Server state management
Axios	HTTP client
Lucide React	Icons
React Hot Toast	Notifications

Backend

Technology	Purpose
Django 5.x	Web framework
Django REST Framework	API layer
SQLite	Database
JWT (SimpleJWT)	Authentication
Meta Llama 3.3 70B	AI conversations & triage
OpenAI Whisper	Speech-to-text
OpenAI TTS	Text-to-speech
Together AI	LLM API provider

Deployment

Service	Component
Vercel	Frontend hosting
Azure App Service	Backend hosting
Azure	SQLite database

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Features

For Mothers

Voice-Based Onboarding

• Speak naturally to set up your profile
• AI extracts and saves your health information
• No typing required - fully accessible

Daily Pregnancy Program

• 40 weeks of curated educational content
• Lessons tailored to your current gestational week
• Wellness tasks and health tips
• Video content from trusted sources

AI Health Companion "Bloom"

• 24/7 conversational health support
• Symptom analysis with urgency classification
• Context-aware responses based on pregnancy week
• Voice input and audio responses

Health Tracking

• Daily mood and symptom logging
• Kick counter (for 20+ weeks)
• Weight and vitals tracking
• Appointment management

Life Passport

• Comprehensive health timeline
• Shareable with healthcare providers
• Complete pregnancy history

Token Rewards

• Earn tokens for daily lessons (+5)
• Earn tokens for health check-ins (+5)
• Earn tokens for wellness tasks (+5)
• 7-day streak bonus (+20)
• Convert tokens to Naira (10 tokens = ₦1)

For Healthcare Organizations

Patient Management

• Invite mothers to connect via email
• View connected patients' health data
• Access Life Passports with permission

AI-Powered Reports

• Health reports filtered by urgency level
• Critical alerts for immediate attention
• Automated symptom analysis

Dashboard

• Overview of all connected patients
• Pregnancy progress tracking
• Upcoming appointments

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User Flows

Mother Signup Flow

1. Sign Up (email, password, phone)
        ↓
2. Voice Onboarding
   - AI asks about age, blood type, due date
   - Collects emergency contact info
   - Saves health conditions
        ↓
3. Add First Child/Pregnancy
   - Enter due date or birth date
   - Set nickname
        ↓
4. Dashboard
   - Access daily lessons
   - Track health
   - Chat with Bloom

Healthcare Organization Flow

1. Organization Sign Up
   - Register hospital/clinic details
   - Verify credentials
        ↓
2. Invite Patients
   - Search by email
   - Send connection request
        ↓
3. Patient Accepts
   - Mother receives invitation
   - Chooses to share data
        ↓
4. Access Patient Data
   - View Life Passport
   - See health reports
   - Monitor pregnancy progress

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Project Structure

bloom/
├── frontend/                    # React frontend application
│   ├── src/
│   │   ├── api/                # API client functions
│   │   │   ├── auth.js         # Authentication API
│   │   │   ├── ai.js           # AI conversation API
│   │   │   ├── children.js     # Children/pregnancy API
│   │   │   └── ...
│   │   ├── components/
│   │   │   ├── common/         # Reusable UI components
│   │   │   ├── layout/         # Layout components (Navbar, etc.)
│   │   │   └── voice/          # Voice recording components
│   │   ├── context/
│   │   │   └── AuthContext.jsx # Authentication state
│   │   ├── pages/
│   │   │   ├── auth/           # Login, Signup, Onboarding
│   │   │   ├── mother/         # Mother dashboard pages
│   │   │   ├── doctor/         # Doctor portal pages
│   │   │   ├── organization/   # Hospital/clinic pages
│   │   │   └── admin/          # Admin panel pages
│   │   └── index.css           # Tailwind theme config
│   ├── package.json
│   └── vite.config.js
│
├── backend/                     # Django backend application
│   ├── apps/
│   │   ├── users/              # User auth & profiles
│   │   ├── children/           # Pregnancy/child management
│   │   ├── ai/                 # AI services (Llama, Whisper, TTS)
│   │   ├── health/             # Health logs, kicks, reports
│   │   ├── daily_program/      # 40-week content & progress
│   │   ├── tokens/             # Token rewards system
│   │   ├── withdrawals/        # Token withdrawal
│   │   ├── organizations/      # Healthcare CRM
│   │   ├── passport/           # Life Passport
│   │   ├── payments/           # ALATPay integration
│   │   └── sms_api/            # SMS notifications
│   ├── mamalert/               # Django project settings
│   ├── manage.py
│   ├── requirements.txt
│   └── startup.sh              # Azure startup script
│
├── CLAUDE.md                   # AI assistant instructions
└── README.md

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API Documentation

Authentication

Endpoint	Method	Description
/api/auth/signup/	POST	Register new user
/api/auth/login/	POST	Login and get JWT token
/api/auth/me/	GET	Get current user profile
/api/auth/me/	PATCH	Update user profile

Children/Pregnancy

Endpoint	Method	Description
/api/children/	GET	List all children
/api/children/	POST	Add new child/pregnancy
/api/children/{id}/	GET	Get child details
/api/children/{id}/	PATCH	Update child

Daily Program

Endpoint	Method	Description
/api/daily/{childId}/today/	GET	Get today's program
/api/daily/{childId}/{progressId}/complete-lesson/	POST	Complete lesson
/api/daily/{childId}/{progressId}/complete-task/	POST	Complete task
/api/daily/{childId}/{progressId}/checkin/	POST	Submit health check-in
/api/daily/{childId}/videos/	GET	Get educational videos

AI Conversations

Endpoint	Method	Description
/api/ai/conversation/start/	POST	Start new conversation
/api/ai/conversation/message/	POST	Send text or voice message
/api/ai/conversation/{id}/complete/	POST	Complete conversation
/api/ai/transcribe/	POST	Transcribe audio only

Health Tracking

Endpoint	Method	Description
/api/health/{childId}/logs/	GET	Get health logs
/api/health/{childId}/logs/	POST	Create health log
/api/health/{childId}/kicks/	GET	Get kick sessions
/api/health/{childId}/kicks/start/	POST	Start kick session
/api/health/{childId}/kicks/{id}/record/	POST	Record a kick

Organizations (Healthcare CRM)

Endpoint	Method	Description
/api/organizations/signup/	POST	Register organization
/api/organizations/patients/	GET	List connected patients
/api/organizations/patients/invite/	POST	Invite patient by email
/api/organizations/patients/{id}/	GET	Get patient details
/api/organizations/reports/	GET	Get health reports

Tokens & Withdrawals

Endpoint	Method	Description
/api/tokens/balance/	GET	Get token balance
/api/tokens/transactions/	GET	Get transaction history
/api/withdrawals/	POST	Request withdrawal
/api/withdrawals/	GET	Get withdrawal history

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Quick Start

Prerequisites

• Python 3.11+
• Node.js 18+
• npm or yarn

Backend Setup

# Navigate to backend
cd backend

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Linux/Mac
# or: venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

# Run migrations
python manage.py migrate

# Seed educational content
python manage.py seed_content

# Seed demo data (optional)
python manage.py seed_all

# Start development server
python manage.py runserver

Frontend Setup

# Navigate to frontend
cd frontend

# Install dependencies
npm install

# Start development server
npm run dev

Environment Variables

Backend .env

# Django
SECRET_KEY=your-django-secret-key
DEBUG=True

# AI Services
TOGETHER_API_KEY=your-together-ai-key
OPENAI_API_KEY=your-openai-key

# CORS (for local development)
CORS_ALLOWED_ORIGINS=http://localhost:3000,http://localhost:5173
CORS_ALLOW_ALL=True

# Database (production)
DATABASE_URL=postgres://...  # Optional, uses SQLite by default

# Payments (optional)
ALATPAY_PUBLIC_KEY=your-key
ALATPAY_SECRET_KEY=your-key
ALATPAY_BUSINESS_ID=your-id

# SMS (optional)
AFRICASTALKING_USERNAME=your-username
AFRICASTALKING_API_KEY=your-key

Frontend .env

VITE_API_URL=http://localhost:8000/api

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Demo Accounts

Role	Email	Password	Access
Mother	demo@bloom.ng	demo1234	Mother dashboard, daily lessons, chat
Admin	admin@bloom.ng	admin1234	Admin panel, user management
Doctor	doctor@bloom.ng	doctor1234	Doctor portal, patient reports
Hospital	lagoshospital@bloom.ng	password123	Organization dashboard, CRM

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Deployment

Frontend (Vercel)

1. Connect your GitHub repository to Vercel
2. Set environment variables:
   • VITE_API_URL=https://your-backend-url.azurewebsites.net/api
3. Deploy

Backend (Azure App Service)

1. Create Azure App Service (Python 3.11)
2. Configure deployment from GitHub
3. Set environment variables in Azure Configuration
4. Push to trigger deployment:

cd backend
git push azure main

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AI Architecture

Conversation Types

Type	Purpose	Data Extracted
onboarding	Initial profile setup	Age, blood type, emergency contact, health conditions
add_child	Add pregnancy/child	Due date, nickname, pregnancy details
chat	General health chat	Symptoms, concerns, questions
birth	Birth registration	Birth date, weight, delivery type

Urgency Classification

The AI classifies health concerns into four levels:

Level	Description	Action
Critical	Life-threatening symptoms	Immediate medical attention
Urgent	Concerning symptoms	See doctor within 24-48 hours
Moderate	Minor concerns	Monitor and follow up
Normal	Expected pregnancy symptoms	Reassurance and education

Voice Flow

User speaks → Frontend records audio (WebM/M4A)
     ↓
Audio sent to backend (multipart/form-data)
     ↓
OpenAI Whisper transcribes to text
     ↓
Llama 3.3 70B generates response
     ↓
OpenAI TTS converts to speech
     ↓
Audio URL returned to frontend
     ↓
Audio plays automatically

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Design System

Colors (Tailwind CSS v4)

/* Primary - Pale Pink */
--color-primary-500: #E8A0A0;

/* Secondary - Bloom Green */
--color-bloom-500: #8BC49E;

/* Background - Cream */
--color-cream-100: #FDF8F3;

/* Dark - Text */
--color-dark-900: #1A1A2E;

Design Rules

• No gradients (solid colors only)
• Exception: Image overlays for text readability
• Rounded corners: rounded-2xl for cards
• Floating pill buttons with backdrop blur
• Subtle shadows: shadow-lg shadow-dark-900/5

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Testing

Run Backend Tests

cd backend
python manage.py test

Run E2E Test

cd backend
python e2e_test.py

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Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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Built With Meta AI

This project uses Meta Llama 3.3 70B Turbo via Together AI for:

• Conversational health companion
• Symptom analysis and triage
• Structured data extraction from voice input
• Context-aware pregnancy guidance
• Health report generation

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License

MIT License - see LICENSE for details.

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Acknowledgments

• Meta AI for Llama 3.3 70B Turbo
• OpenAI for Whisper and TTS
• Together AI for LLM hosting
• The Nigerian healthcare workers inspiring this solution