OpenCHS AI Service is an advanced AI-driven solution for voice processing and case prediction.
It enables automated transcription, translation, and case classification, enhancing efficiency in omnichannel call management and case management systems.
This service is part of the OpenCHS (Open Child Helpline System) ecosystem — an open-source Digital Public Good developed and maintained by BITZ IT Consulting Ltd in collaboration with UNICEF and government partners across Eastern and Southern Africa.
- 🎙 Voice Recognition: Converts speech to text using AI-powered speech-to-text models (Whisper, wav2vec2, or similar).
- 🌐 Translation: Translates transcribed text into English or other supported languages to assist multilingual service delivery.
- 🧠 NLP-Based Case Prediction: Classifies and prioritizes cases using Natural Language Processing (NLP) for faster triage.
- ⚙️ Workflow Automation: Uses Celery and task orchestration for scalable background processing.
- 🗄 Data Storage & Visualization: Saves processed data in MinIO/S3 and provides structured outputs for analytics and dashboards.
Handles the complete data processing workflow:
ingestion/— Fetches and prepares raw audio data.transcription/— Converts speech to text.translation/— Translates non-English text.nlp/— Applies NLP models for classification.orchestration/— Coordinates pipeline tasks using Celery.storage/— Manages MinIO/S3 storage.
Houses AI models used in the processing pipeline:
voice_recognition/— Speech-to-text models.translation/— AI translation models.case_prediction/— NLP classification models.
Backend APIs and orchestration:
api/— RESTful endpoints for model access.authentication/— Handles user access and tokens.logging/— Tracks events and errors.
Front-end dashboards for visualization and case management.
Deployment and CI/CD configurations:
docker/— Container setup files.k8s/— Kubernetes manifests.ci_cd/— CI/CD pipeline configurations.
| Document | Description |
|---|---|
| PROJECT_CHARTER.md | Project objectives and scope. |
| DATA_PIPELINE.md | Data processing and workflow overview. |
| ARCHITECTURE.md | Technical architecture of the system. |
| SECURITY.md | Security best practices and data protection measures. |
| GOVERNANCE.md | Project governance and roles. |
| TESTING_STRATEGY.md | Approach for testing AI models and APIs. |
| DEPLOYMENT_GUIDE.md | Deployment setup and environment configuration. |
| ROADMAP.md | Upcoming features and development milestones. |
Ensure you have the following installed:
- Python 3.11+
- Node.js 18+
- Docker & Docker Compose
- Redis & Celery (for asynchronous orchestration)
- MinIO or compatible S3 object storage
# Clone the repository
git clone https://github.com/openchlai/ai.git
cd ai
# Create virtual environment
python3 -m venv venv
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt