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Visual data management made easy

Superhuman Vision revolutionizes how the world sorts and manages vast media assets.

Asset Management

AI powered asset management

Instantly categorize visual content as it is uploaded to your platform, making it quickly searchable via intuitive AI models.

Super easy to install

Lightweight solutions that integrate seamlessly with any system

Streamlined productivity

Prioritizes content to accelerate workflows & reduce search times

Demographic analysis

Identifies user base of your data, including age, industry & more

Hear it from our customers

Asset Management

Leverage AI-powered asset management solutions that streamline and accelerate your workflows.

Asset Management
Press & Broadcasting
Coming Soon

Empower journalists with tagged visual archives

Press & Broadcasting
Coming Soon

Empower journalists with tagged visual archives

Video Services
Coming Soon

Moderate & manage video content with ease

Video Services
Coming Soon

Moderate & manage video content with ease

Stock Photography
Coming Soon

Easily identify relevant visuals for purchase

Stock Photography
Coming Soon

Easily identify relevant visuals for purchase

Creative Platforms
Coming Soon

Source the best visual content

Creative Platforms
Coming Soon

Source the best visual content

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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.