A renowned Swiss Digital Asset Management firm wants to use AI to improve its asset management platform. Their goal was to assist B2B clients in successfully managing their assets and reclaiming important time. The Digital Asset Management business intended to assist its clients by enhancing the capacity to tag and categorize material to improve discoverability during the critical search phase. They were well aware that their consumers struggled to discover the proper information and wasted important time searching in vain. Frequently, media is labeled by one individual who has a different perspective than another. One individual may tag a picture with "scuba diver," while another may just tag it with "diver." The company's objective was to automate the asset tagging process and enhance the way user photos are tagged and categorized to boost operational efficiency and improve user experience.
To speed up the metadata tagging process and increase accuracy, the firm turned to Clarifai's computer vision and AI machine learning platform. The Digital Asset Management business conducted tests with a variety of AI providers, and Clarifai came out on top in terms of accuracy, simplicity of use, and the company's high level of service. Clarifai decided to invest in its computer vision and deep learning platform after seeing how well their pre-trained generic model performed. With the aid of automatic metadata creation, the firm can now auto-tag its material. Clarifai's AI-assisted tagging generates labeling recommendations that human data annotators would overlook. This enhances the quality of digital asset tagging and classification, making it easier for users to discover files.
As a result, they now spend less time labeling their visual assets. Clarifai's deep learning AI technology has helped the business improve its platform by clearly recognizing the contents of pictures and videos, making it easier and faster for clients to utilize its digital asset management platform.
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