🏥 Kliniq

AI-Powered Multilingual Healthcare Platform for Nigeria

Breaking language barriers in healthcare through intelligent AI triage, voice-enabled consultations, and seamless patient-clinician communication in English, Hausa, Igbo, and Yoruba.

View Demo • The Problem • Our Solution • Repositories • Quick Start

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🎥 Demo

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🌍 The Problem

In Nigeria, over 60% of the population speaks indigenous languages as their primary language, yet healthcare systems operate predominantly in English. This creates critical barriers that cost lives:

Challenge	Impact
🚫 Language Barrier	Patients can't accurately describe symptoms
⏰ Delayed Care	Miscommunication leads to misdiagnosis
🏥 Access Inequality	Rural and elderly populations excluded
📝 Information Gap	Medical records incomprehensible to patients
👩‍⚕️ Clinician Overload	Routine queries overwhelm healthcare workers

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💡 Our Solution

Kliniq is a comprehensive healthcare platform powered by N-ATLaS (Nigerian-Adapted Translation and Language System) — our custom multilingual AI model fine-tuned for Nigerian languages and medical terminology.

🧠 N-ATLaS: The AI Engine

Our custom LLM understands and responds in:

• 🇬🇧 English
• 🇳🇬 Hausa (spoken by 70M+ Nigerians)
• 🇳🇬 Igbo (spoken by 45M+ Nigerians)
• 🇳🇬 Yoruba (spoken by 45M+ Nigerians)

✨ Key Features

👤 For Patients 💬 AI health assistant in your language 🎙️ Voice-first interface with transcription 🏥 Link to multiple hospitals via codes 📅 Book and manage appointments 📊 Track health vitals and history

👩‍⚕️ For Clinicians 📊 Smart dashboard with AI triage 👥 Patient management with full history 🔍 AI-powered patient analysis ✅ Appointment approval workflow 🏆 Gamification for engagement

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📦 Repositories

This project consists of two repositories:

Repository	Description	Tech Stack
Kliniq Frontend	Next.js web application with patient and clinician dashboards	Next.js 16, React 19, TypeScript, Tailwind CSS 4
Kliniq API	FastAPI backend with N-ATLaS AI integration	FastAPI, PostgreSQL, SQLAlchemy, Modal

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🚀 Quick Start

Prerequisites

• Node.js 18+
• Python 3.11+
• PostgreSQL 15+

1. Clone Both Repositories

# Clone frontend
git clone https://github.com/Twilight-Techy/kliniq-ui.git

# Clone backend
git clone https://github.com/Twilight-Techy/kliniq-api.git

2. Setup Backend

cd kliniq-api

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

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your database credentials

# Run migrations
alembic upgrade head

# Seed test data
python -m scripts.seed_test_data

# Start server
uvicorn src.main:app --reload --port 8001

3. Setup Frontend

cd kliniq-ui

# Install dependencies
npm install

# Configure environment
echo "NEXT_PUBLIC_API_URL=http://localhost:8001" > .env

# Start development server
npm run dev

4. Access the Application

• Frontend: http://localhost:3000
• API Docs: http://localhost:8001/docs

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🔑 Demo Accounts

Role	Email	Password
👤 Patient	dayo@test.com	Test1234!
👩‍⚕️ Nurse	ngozi@test.com	Test1234!
👨‍⚕️ Doctor	emeka@test.com	Test1234!

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🏗️ Architecture

┌─────────────────────────────────────────────────────────────────┐
│                         USER INTERFACES                          │
│  ┌──────────────────────┐    ┌─────────────────────────────────┐ │
│  │   Patient Dashboard  │    │      Clinician Dashboard        │ │
│  │   • AI Chat          │    │      • Nurse Portal             │ │
│  │   • Appointments     │    │      • Doctor Portal            │ │
│  │   • Health Records   │    │      • Patient Management       │ │
│  └──────────────────────┘    └─────────────────────────────────┘ │
└───────────────────────────────┬─────────────────────────────────┘
                                │
                                ▼
┌─────────────────────────────────────────────────────────────────┐
│                        KLINIQ API (FastAPI)                      │
│  ┌─────────────┐  ┌──────────────┐  ┌────────────────────────┐  │
│  │    Auth     │  │   Dashboard  │  │      Clinician         │  │
│  │   Module    │  │    Module    │  │       Module           │  │
│  └─────────────┘  └──────────────┘  └────────────────────────┘  │
│                            │                                     │
│                            ▼                                     │
│              ┌─────────────────────────────┐                     │
│              │      N-ATLaS LLM Service    │                     │
│              │  • Multilingual Chat        │                     │
│              │  • Symptom Triage           │                     │
│              │  • Tool Calling (Actions)   │                     │
│              └─────────────┬───────────────┘                     │
└────────────────────────────┼────────────────────────────────────┘
                             │
                             ▼
              ┌─────────────────────────────┐
              │      Modal Cloud GPU        │
              │   (N-ATLaS Model Hosting)   │
              └─────────────────────────────┘

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🏆 Awarri Developer Challenge 2025

This project was built for the Awarri Developer Challenge 2025 demonstrating:

Criteria	How We Address It
Social Impact	Breaking language barriers in Nigerian healthcare
Technical Innovation	Custom N-ATLaS multilingual AI model
User Experience	Beautiful, accessible, voice-first design
Scalability	Enterprise-ready architecture with Modal cloud AI
Real-World Applicability	Solving actual clinical workflow challenges

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👨‍💻 Team

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📄 License

MIT License - See LICENSE for details.

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Built with ❤️ for Nigerian Healthcare

_{Awarri Developer Challenge 2025}