زكرياء ل.

I worked on developing a complete SaaS platform featuring multi-tenancy, a full billing system, and a suite of business management tools. The project included implementing tenant isolation with support for custom domains and subdomains, customizable branding, and advanced configuration controls. I designed and integrated key financial modules such as invoices, expenses, budgets, sales tracking, and vendor management. Additionally, I built a robust user and employee management system with RBAC, activity logs, internal requests, and real-time notifications. The platform was architected for scalability using Laravel 11, FilamentPHP, and Spatie packages for permissions, activity logging, and multi-tenancy, with supporting technologies including MySQL, Tailwind CSS, Blade, and Laravel Breeze (2FA).

I developed a multilingual question-and-answer platform featuring structured content organization, categories, tagging, and comprehensive moderation tools. The system included an ultra-fast full-text search engine powered by Meilisearch to ensure responsive question discovery and accurate relevance ranking. I built content and admin management tools using FilamentPHP for handling questions, answers, pages, sitemaps, and media assets. The platform also incorporated background processing, notifications, automated sitemap generation, and SEO-optimized routing to enhance search visibility. In addition, I implemented full internationalization and localization support, along with accessibility and progressive enhancement for a smooth user experience. The solution was built with Laravel, PHP, FilamentPHP, Meilisearch, MySQL, Tailwind CSS, Inertia + React, Blade, Laravel Breeze (auth/2FA), queues/workers, and Spatie packages.

I designed and developed a complete Point of Sale (POS) system for Android, including backend services, secure authentication, and a responsive mobile interface. The solution was built using Node.js and Express for the server-side APIs, Flutter and Dart for the Android application, JWT for secure access control, and MongoDB for data storage, with development and deployment managed through Android Studio.

I developed a CNN-based object recognition application that included dataset preprocessing, model training, and integration of prediction results into a Django web interface. I managed image data using SQL databases and leveraged OpenCV for image processing and handling throughout the pipeline. The project was built using Python, TensorFlow, OpenCV, CNN architectures, Django, and SQL.

During my internship at Elevvo Pathways, I analyzed various datasets and developed machine learning models for both classification and forecasting tasks. I worked on several applied projects, including traffic sign recognition, forest cover classification, loan approval prediction, and sales forecasting. These projects were implemented using Python with Scikit-learn, Pandas, NumPy, and Seaborn for data processing, modeling, and visualization.