VSN’s Media Asset Management software, VSNExplorer MAM, offers all the necessary tools to manage the entire media life-cycle. Its GUI is based on HTML5, allowing users to manage media files within different storage units, also in the Cloud, and to access the platform from any browser and operating system. In addition, its highly scalable and open architecture enables the integration of VSNExplorer MAM with any software and hardware available in the market. This solution is available on-premise or in the Cloud, as pay-per-use in SaaS platforms such as Windows Azure, Amazon or Private Cloud. This model grants higher speed and more flexibility, reducing costs and time-to-market rates.
VSNExplorer MAM has also been integrated with the Artificial Intelligence systems of IBM, Google, Microsoft Azure and Etiqmedia for automatic metadata detection and content cataloging. This systems can also be “trained” (known as machine learning) to automatically detect informacion adapted to user’s needs, such as people first unknown to the system who will be automatically recognized from that moment on. Apart from facial recognition and objects analysis, thanks to AI systems VSNExplorer MAM can also perform advanced searches relying on metadata, automatic speech-to-text, translation and subtitling, advanced Cloud transcoding to different formats or even help on content moderation processes through the detection of sensitive or adult content, among others.
VSNExplorer MAM now includes Wedit, the web video editor integrated within VSNExplorer platform, to boost collaborative work and increase efficiency in media management and video editing through its cloud-based functionalities, whether assets are stored in deep archive, nearline or online files. 100% HTML5, Wedit allows journalists and editors to easily locate and edit media files within a single interface, without necessary changing to an NLE.
Finally, VSNExplorer MAM is completely integrated with the main social media platforms, such as Facebook, YouTube and Twitter, allowing users to share content directly from their MAM interface, automatically converting media files into MP4 and completing the metadata required by these platforms with the metadata detected from each media file.
