EyeQuant Embraces Leading Neuroscience and AI to Give Accurate Learnings for How Users Will Respond To Your Designs.

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  • EyeQuant is a machine learning based design analysis technology that instantly predicts how users are going to perceive any design across devices. All it takes is an image file.
  • The predictions achieve between 85% (attention prediction) and 90% (clarity and excitingness scores) accuracy when compared to large-scale human studies.
  • That’s about 90% of the accuracy of a full study at less than 0.1% of the time needed!
Download >50 Accuracy Studies

Starting with real world data, we build
ML models to provide instant predictions:

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1. Large Scale User Studies

In the first step, we gather data in large-scale human studies with thousands of subjects, both in our associated eye-tracking labs and through crowdsourced online panels.

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2. Machine Learning

Secondly, we use machine learning to find and model the underlying perceptual patterns in the data - these range from low level features like color contrast to high level, top-down mechanisms. 

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3. Instant Predictive Results

The best performing models get productized for our customers and provide predictive results that are both extremely fast and can be applied at scale.

Research Partners & Associations

EyeQuant was spun out of breakthrough foundational research at the Neurobiopsychology Lab at the Institute of Cognitive Science at the University of Osnabrück in Germany, one of Europe's leading Cognitive Science research institutions. 
We further collaborate with various research institutations around the world, including the Horizon2020 supported consortium NextGenVis which is aiming to train the Next Generation of European Visual Neuroscientists. 

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Interested in working with EyeQuant's technology in academia?
We provide free API access to selected researchers.
Do get in touch via research (at) eyequant (dot) com.

Trusted by world-class CRO, UX and AdTech teams at:
  • Google
  • Canon
  • Epson
  • RBS
  • Newegg
  • Possible