Software that predicts employee burnout through language


Imagine being at your computer, busy with work and on the brink of burnout, when you receive a message that tells you to relax and take the rest of your day off, for the benefit of your mental health.

This is the goal for Erudit, a software company that uses algorithms to predict and prevent employee burnout.

In the same way that Netflix strives to understand each individual user and offers them options tailored for them, Erudit wants to do the same to reduce employee burnout, understanding what they need to stay mentally healthy and well.

Listen to this podcast on Spotify, Anchor, Apple Podcasts, Breaker, Google Podcasts, Stitcher, Overcast, Listen Notes, PodBean, and Radio Public.

To understand how this software works and how it was created, we are joined by Ricardo Michel Reyes, Erudit AI co-founder and AI director, alongside Pablo Gil Torres, the CPO of Erudit.

In this episode you will learn the differences in difficulty when identifying meaning between Germanic languages such as German, English, Dutch, and Romance languages, such as Spanish, Portuguese, French, and Italian.

You will also learn about the origins of how they created their natural language processing algorithm and how their software advises companies when an employee is close to burnout.

In addition to this Torres and Reyes explain how they developed their own psychological theory named Semantic Analysis, based on math and linguistics.

Disclosure: This episode includes a client of an Espacio portfolio company

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Sam Brake Guia
Sam is an energetic and passionate writer/presenter, always looking for the next adventure. In August 2016 he donated all of his possessions to charity, quit his job, and left the UK. Since then he has been on the road travelling through North, Central and South America searching for new adventures and amazing stories.