Everything needed to understand, run and contribute to ARWE — versioned and public.
ARWE Overview v2026.08
ON THIS PAGE
Mission
Domains
Systems
Project ARWE is an open-source technology ecosystem created by Henok Akriso, building interconnected systems for Digital Ethiopia. It is not a single application and not a collection of unrelated repositories — it is an ecosystem of specialized systems sharing common engineering principles.
Core domains: government, education, digital identity, land, procurement, cybersecurity, artificial intelligence, robotics, digital twins, public infrastructure and future technology.
Architecture v2026.08
ARWE spans three technology layers — WEB (HTML/CSS/JS → PHP), AI (Python services) and SYSTEMS (C/C++ embedded & robotics). Systems are independently deployable but composable through interoperability contracts. Shared capabilities include authentication, identity, notifications, audit, analytics, verification, AI services and data services.
See the full architecture page for relationship contracts between systems.
Development Principles
Use the right language for the right layer. No project must use every technology.
Local-first. Ethiopian calendar, administrative structures, languages and bandwidth realities are design inputs, not afterthoughts.
Open by default. Source, architecture and roadmap are public.
Evolve over years. Systems follow the public roadmap rather than one-off releases.
Installation
Each repository contains its own setup guide. Typical web-layer system:
shell
git clone https://github.com/henokakriso/arwe-locify.git
cd arwe-locify
composer install # PHP dependencies
php -S localhost:8080 # local development server
Systems-layer projects (C/C++) document their toolchain per platform in their respective READMEs.
Security
Security practices apply across all systems: secure authentication, authorization, input validation, session security, audit logging, encryption where appropriate and secure API design. Vulnerabilities are handled through responsible disclosure — see the security page. Implementation details are intentionally kept out of public landing materials.
API
Web-layer systems expose versioned HTTP APIs using JSON. API references are generated from source per repository. Cross-system calls follow the interoperability contracts defined in the architecture documentation.
Database
Schemas are documented per repository with migration scripts. Shared conventions: audit tables on institutional records, soft deletion for citizen-facing records, and localization-ready reference data.
Localization
ARWE treats Amharic, Afaan Oromo and English as first-class interface languages. The Ethiopian calendar is supported natively alongside Gregorian dates. Translation files live inside each repository under /lang.
Contribution
Read the contribution guide, open an issue before large changes, and submit pull requests against the relevant repository. All contributions are reviewed under each project's quality standards.
Licensing
Licensing is declared per repository. The ecosystem default favors permissive open-source licenses that keep the technology public while allowing institutional adoption.
GOVYX ACTIVE
AI-assisted government operations, task monitoring, accountability, KPI management, institutional workflows, and decision support.
A digital local-government platform for citizen services, document requests, applications, appointments, status tracking, notifications, identity workflows, and digital verification.
Category
Digital Kebele & Identity
Languages
PHP · Python · HTML · CSS · JavaScript
Areas
Citizen services, Document requests, Applications, Appointments, Status tracking, Digital verification
A transparent digital infrastructure for land records, procurement workflows, verification, transaction history, and auditable institutional processes.
Category
Land & Procurement
Languages
C · C++ · Python · PHP
Areas
Land records, Procurement workflows, Verification, Transaction history, Auditable processes
An AI-driven digital twin platform exploring persistent personal intelligence, contextual reasoning, knowledge management, and human-computer interaction.
Category
Digital Twin AI
Languages
Python · C++ · JavaScript
Areas
Personal digital twins, Contextual reasoning, Knowledge management, Human-computer interaction, Memory architectures