Software 19 would be a landmark upgrade for FOCI. And it would be in Android, as we are using a leapfrog software development strategy (alternate updates on iOS & Android) so that we can integrate feedback from users from alternate platforms, to improve product development.

So for the Android update, apart from iOS’s software update 18, which includes:

  • 4 times the performance upgrade from the old FOCI version
  • Machine Learning upgrade boost that reads 150% more emotion data
  • Negative Emotion Analytics: that evaluate risks of frustration, distractibility, procrastination, burnout and anxiety that impact focus
  • Key cognitive metrics: mental performance, tension overload level that could really give you a major boost to your productivity


This main game changer in software update 19 (Android) will be biofeedback upgrade. 

The greatest success and the greatest failure for FOCI so far, has been the biofeedback. 


It is such a success, because it really works (with a catch), that it is able to help us actively modulate attention and tune into focus. It is revolutionary!

It is most gratifying that so many users are already using biofeedback for more than 5 hours a day! The benefit is clear, it is much easier to get into flow using biofeedback. My personal experience has been 80% of my flow has been assisted by biofeedback. I’m not the only one here. Most of my teammates, and many many more backers, have already tasted its potential.

 negative emotion analytics

However, the greatest failure for FOCI so far, has also been the biofeedback. 

The catch is that biofeedback has been embedded with lots of nonlinearity, inherent with a causal data analysis system that makes it hard for users to grasp the intuition, especially when one has limited experience with any form of physiological contemplative exercises. 

In other words if one has limited experience with mindfulness (a subset of mindfulness to be exact),  which involves the intuition of controlling parasympathetic and sympathetic balance, the current biofeedback is very hard to use.


Luckily, machine learning is coming to the rescue. We are working on breaking this nonlinearity inherent in the causal system with ML to approximate a non-causal system. In friendlier terms, it would make educated guesses based on your past, so that you would feel that the biofeedback is way easier to use than before.

Then you would have a taste of FOCI’s true potential in boosting focus. We are going to make it happen.


Best wishes

Mick & The FOCI Team

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