Hashlab

Masonry Gallery is a visual showcase project that implements a Masonry-style grid to display images in an organic, Pinterest-like layout. The interface emphasizes smooth loading, responsive behavior, and elegant arrangement of media content for an engaging browsing experience. Implemented with Next.js, TypeScript, and Tailwind CSS, the project focuses on efficient layout rendering, performance, and accessibility. Its structure allows for future enhancements such as lazy loading, filtering, and dynamic content sourcing without breaking the core grid behavior.

Team Delivery is a website developed for a delivery company, focused on presenting its services, coverage, and business offering in a clear and professional way. The goal was to build a trustworthy online presence that allows potential clients to quickly understand the company’s logistics services and get in touch. The website is built using Next.js, TypeScript, and Tailwind CSS, with an emphasis on performance, responsive layouts, and clarity of information. The architecture supports future expansion, such as adding service details, pricing sections, or order and inquiry forms.

Attendance App is a system designed for attendance tracking with an emphasis on automated device identification. In addition to the web interface, the solution includes a Python script running in the background, responsible for collecting MAC addresses of devices present on the network, enabling more reliable presence detection without manual user input. The frontend is built with Next.js, TypeScript, and Tailwind CSS, focusing on clarity, reliability, and straightforward data presentation. The architecture separates data collection from visualization, allowing the Python-based collector to operate independently while the frontend remains lightweight and easy to extend with reporting, filtering, or administrative views.

Chat App is a communication platform developed as part of a project focused on online safety and grooming prevention. The application provides a structured chat environment that can serve as a foundation for detecting and addressing risky behavior, while maintaining clear communication flows between users. The system includes a backend built with PHP and MySQL, containerized using Docker, and a Vue.js frontend styled with Bootstrap. While the architecture is prepared for future extensions—such as AI-based analysis of voice messages to detect suspicious activity—the current implementation focuses on reliable messaging, data handling, and a clear separation between frontend and backend responsibilities.

Bevos is a corporate website created for a construction company to present its services, completed projects, and professional capabilities online. The site aims to provide a modern, clear, and trustworthy presentation of the company’s expertise in residential construction, earthworks, and material transportation across the Spiš region. The website is built using Next.js, TypeScript, React, and Tailwind CSS, with content managed through Sanity CMS for flexibility and future content updates. The architecture emphasizes performance, responsiveness, and clean UI so that potential clients can quickly explore services and contact the company, while maintaining scalability for additional sections or portfolio enhancements.

Pixel AI is a frontend interface designed to work with a Python-based AI backend that enhances image quality. The application provides users with a simple and responsive interface to upload images and receive improved results from the AI service, focusing on usability and clarity. Built with modern web technologies, the frontend emphasizes performance and clean UX, serving as a lightweight gateway between users and the AI processing system. The architecture is prepared for future features such as batch uploads or visual previews of enhancements.