We developed a WebChat application powered by DeepL AI for real-time message translation. Built with the MERN stack and Sockets.io, the system ensured seamless communication. Hosting was secured on a Sakura VPS for reliability.

In response to the client’s requirements, we delivered a cutting-edge online live streaming platform within the specified timeframe. Leveraging Next.js and Node.js, our team built a scalable and efficient system capable of handling high traffic volumes. Web sockets were implemented for real-time communication, ensuring seamless interactions between users. To support the client’s legacy database, we implemented a hybrid database structure combining MongoDB and NoSQL. Live streaming services were powered by AWS IVS (Amazon Interactive Video Service), providing reliable and high-quality streaming capabilities. Real-time leaderboard data was stored and managed using Redis cache, enabling instantaneous updates. Additionally, we integrated Banuba SDK for face AR effects, enhancing user engagement and interactivity.

The solution we propose for the aforementioned challenge is a sophisticated web-based system designed to streamline the scheduling and management of nursing/rehab visit plans. This comprehensive solution caters to the needs of administrators, visitors (nursing and rehab), as well as care managers external to the company.

The project involves developing a web-based AR application that utilizes image tracking to overlay 3D models onto drink product packaging. The application must be capable of simultaneously tracking multiple product packages and rendering the corresponding 3D models in real-time. Furthermore, users should have the ability to capture screenshots of the AR experience and share them on popular social media platforms such as Instagram, Facebook, and Twitter.