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Easily identify relevant visuals for purchase

Superhuman Vision recognizes new concepts in community photographs and strengthens keywording accuracy.

Stock Photography

Superquick, reliable tagging

Precise keywording of visuals returns select, high-quality matches on stock photo platforms, thus promoting an increase in downloads and payment.

Reduced tagging time

Cuts image key-wording time by up to 50% of other solutions

Content discovery

Identifies visual content with high commercial value

Precise search results

Improved tagging accuracy shows relevant content to clients

Hear it from our customers

Stock Photography
Asset Management
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Visual data management made easy

Asset Management
Coming Soon

Visual data management made easy

Video Services
Coming Soon

Moderate & manage video content with ease

Video Services
Coming Soon

Moderate & manage video content with ease

Creative Platforms
Coming Soon

Source the best visual content

Creative Platforms
Coming Soon

Source the best visual content

Printing Services
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Next-gen, AI-powered customer experience

Printing Services
Coming Soon

Next-gen, AI-powered customer experience

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Metadata Mastery

FREE training from the experts at Mobius Labs

Short videos  |  Webinars  |  Exclusive Previews  
Dominic Rüfenacht - Head of Science | Co-founder bei Mobius Labs GmbH
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.