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Editshare - Enhancing EditShare’s flow media asset management with Automated AI

Editshare - Enhancing EditShare’s flow media asset management with Automated AI


Context-rich image analysis to boost revenue

February 16, 2023
May 2, 2022
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Optimizing visual content with rich keywords can change the game

Image tagging has become one of the most popular AI technologies for sorting and categorizing large amounts of visual content. But in order to make the most of archives and promote revenue increase, businesses need to be able to do much more with AI than simply detecting and sorting images by objects and faces.

Superhuman Vision supercharges visual archives by adding rich, contextual tags.

This means tagging visuals with abstract concepts, demographics, brands, atmospheres, themes, photography styles, and much more. Moreover, custom concepts can be easily created on a no-code platform so that images are analyzed for specific themes using granular terms that are important to unique business.

The result?

-Simplifying workflows by improving search experience

-Maintaining brand consistency and brand compliance

-Reducing shopping cart abandonment

…to just name a few.

Whether it is broadcasting houses, press agencies, creative platforms, web-to-print services, or asset management systems, Superhuman Vision finds practical applications for any business need.

Curious to see more of our tech in action? Check out our demo or contact us at to discover how we can help your business boost revenues and improve workflows.

Customer details
Written by
Trisha Mandal
Edited by
Illustrated by
Xana Ramos

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Mobius Labs GmbH is receiving additional funding by the ProFIT program of the Investment Bank of Berlin. The goal of the ProFIT project “Superhuman Vision 2.0 for every application- no code, customizable, on- premise  AI solutions ” is to revolutionize the work with technical images. (f.e.) This project is co-financed by the European Fund for Regional Development (EFRE).

In the ProFIT project, we are exploring models that can recognize various objects and keywords in images and can also detect and segment these objects into specific pixel locations. Furthermore, we are investigating the application of ML algorithms on edge devices, including satellites, mobile phones, and tablets. Additionally, we will explore the combination of multiple modalities, such as audio embedded in videos and the language extracted from that audio.