Learning Analytics
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About NeuroLearn

NeuroLearn is created to bring quantifiable data to the billions of conversations and interactions people have.

How we do that

Biometric sensing with
machine learning analysis

Through biometric sensing using webcams, cameras, and EEG headsets, NeuroLearn is able to measure many data points such as attention, drowsiness, engagement, yawning, nodding, and focus. Our algorithm than takes these inputs, and analyzes them using a proprietary machine learning algorithm to bring actionable advice to speakers about how their audiences are learning (or failing to learn) from them. Our algorithm can

  • Rate the overall effectiveness of the speaker
  • Pinpoint points of confusion in the speech
  • Identify struggling students
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01.
>25k
Universities in the world
7B
Human population
25M
Meetings per day in the US
0
True solutions to handle this

Target Market

For users of various sizes, goals and objectives

Students

  • At any age

Students can track their own cognitive performance. By measuring their learning, they can figure out how to maximize gians in knowledge.

Universities

  • For class insight and improvement

Have class-by-class data on the efficacy of certain professors & classes. Help professors to improve their teaching.

Industry organizations

  • Grow customer base and improve HR

Teach employees necessary skills, ensure productive meetings, and evaluate customer interactions.

02.

A tool with no boundaries

Every interaction has meaning. We all want to be seen, heard, and understood and now there is a tool to measure that.