Marketing stacks in 2017 are expected to get smaller and smarter, largely due to the convergence of artificial intelligence (AI) and machine learning capabilities with legacy systems. Closely towing the trend of empowering marketers with AI technology is Bynder, the leading web-based digital asset management software platform.
Bynder’s DAM module is now laced with cutting-edge AI capabilities, enabling marketers to automate and streamline marketing processes. It is the first DAM platform to leverage Amazon Web Services (AWS) Rekognition, introduced specifically to save marketers hours of time spent in searching, organizing and utilizing digital assets.
“AI is the future of marketing and Bynder is helping shape that landscape,” said Chris Hall, CEO at Bynder. “With our new AI capabilities, Bynder’s software is not just a brand management tool for marketers, but now allows users to save hours of admin labor when uploading and organizing their files, adding exponentially more value.”
Bynder’s AI capabilities will reduce ambiguity in DAM
Deep learning-based image tagging automatically simplifies nomenclature process, providing one common tagging language across DAM platform. Bynder’s DAM module with new AI feature reduces ambiguity about differing terminology for the same thing and time wasted on finding an image you need.
Including AI into DAM solutions relieve the retailers from the pain of manually segregating images with similar contexts. A digital publisher or advertiser frequently uploading thousands of visual assets no longer has to rely on manual tagging and keyword searching to find the accurate file. Marketers can now locate untagged images from DAM libraries using AI-powered automated tagging for content.
In November 2016, AWS launched its Amazon Rekognition, a service that implements deep-learning capabilities to ease image analysis across applications. Rekognition’s API can detect visual aspects in the images, enabling marketers to add sophisticated image search functionalities and visual classifications based on deep learning. In addition to facial recognition and image comparison, marketers can also auto-tag images for simplified organization of digital assets’ libraries.