Uploading files to Razuna is a straightforward and user-friendly process, offering several efficient methods for adding your content to the platform. One of the simplest techniques is to utilize the drag-and-drop feature; you can easily click and drag individual files or even entire folders directly into any designated folder within the browser window. This intuitive action allows for rapid organization and access to your files.
If you prefer a more traditional approach, you can also click on the upload icon located in the bottom right corner of the interface. This will prompt a file selection dialog, enabling you to browse your desktop or file system to select specific files or folders for upload.
Additionally, for those who work with images, Razuna offers a unique capability: if you have an image copied to your clipboard—whether from a screenshot or an online source—you can paste it directly into the browser. The platform will automatically recognize the pasted content and add the image to your chosen folder without any extra steps. This functionality not only streamlines the uploading process but also enhances your productivity.
One effective method of adding existing files and folders to Razuna is by creating a ZIP archive that preserves your desired folder structure along with all relevant files. Upon uploading the ZIP file, Razuna will automatically recreate the folder hierarchy, making organization seamless and efficient.
Additionally, you have the option to send files via email; however, please note that this method has a file size limit of 50MB per email. To ensure optimal performance and usability, we are actively working on introducing new file upload methods in the near future.
For those dealing with larger file uploads, we highly recommend utilizing Razuna Desktop. This application leverages your native network connection for file transfers, resulting in faster and more reliable uploads compared to traditional web browser methods. Doing so can significantly improve your workflow, especially when managing substantial amounts of data.