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Boîte à outils média

sondage sur l'engagement des employés
comment améliorer la culture d'entreprise
Analyse RH
analyse des personnes, 
comment améliorer l'engagement des employés

Employee Engagement and Experience with AI | Culture and Employee Retention | Workplace Culture Consulting

Nous avons développé une plateforme d'Intelligence Artificielle, qui automatise la mesure de la culture et des valeurs de l'entreprise.

ELEFense prédit les modèles et tendances culturels, sans questionnaires et tout en protégeant la vie privée des employés. 

L'objectif du système est d'identifier les modèles et les tendances afin que les entreprises puissent prévenir la toxicité, l'épuisement professionnel et créer une culture d'entreprise positive, et ainsi réduire le taux de désabonnement. 



 

How did ELEFense Start?

ELEFense was founded by managers looking for a way to understand their company culture while preserving employee privacy. When they discovered that no such tool existed, they created one.

 

We understand that managing with technology is hard — after all, we’re the first generation of Executives to have employees who are so connected. Because of this, everything we do is guided by our perspective as Executives trying to guide employees in the digital age.

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How does ELEFense work?

ELEFense is A.I. driven tech that analyses company activity & builds a unified dashboard to demonstrate workplace culture, sentiment, and keywords in order to assess cultural health and trends in real time. ELEFense can be used to:

 

  • Improve service levels

  • Reduce costs

  • Deepen customer loyalty

  • Improve brand management

  • Prevent the risk of abuse, and more

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The ELEFense collection agent collects data directly from each individual endpoint and creates 'anonymous usage statistics' just like a cookie on a website. It does this by collecting text directly at the application level. The system can alert management of negative, positive, hopeful, or risky events & trends to provide an indication of a company's overall health.

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How can I find out more about ELEFense and see the platform?

Feel free to have a read through our product page or contact us.  We are available by mail, phone, or even book a meeting with one of our reps for a demo.

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Can ELEFense help make my organisation happier?

This is the heart and soul of ELEFense. Our system uses the latest AI tech and algorithms to assess the workplace mood by measuring a huge amount of data and recommending the best course of action. ELEFense will help understand how employees rate diversity and inclusion within their company, and then companies can use this information to improve employee happiness.

Please feel free to book a demo to see more.

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What about Privacy?

We believe that employee privacy is a human right and are absolutely dedicated to protecting the privacy of every individual in the company. We are GDPR compliant.

 

Everyone in a modern organization lives and thrives with technology – private and work life is more entwined than ever— which is why we don’t give Executives unfettered access to their employees’ digital activities. ELEFense have put a huge emphasis on privacy and data protection because what we do in our private life is private and does not further our purpose of analysing company culture.

 

How do we protect privacy?

ELEFense listening agent works like a cookie and only analyses internal business interactions, meaning data from employees' private lives is not collected. After analysis, all data is deleted, and all that is kept is the output which is in numerical. Additionally, it is pooled in a department of a minimum of 8 people. Therefore, ELEFense will never look at private doings or reveal any individual data, content, or anything that can give away identity.

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Our artificial intelligence and machine learning algorithms have been created by linguists and phycologists to understand organizational culture without intruding on individual privacy since we believe individual privacy is a basic human right.

 

Regarding the non spoken, this is where the machine learning and deep learning come in. We can pick up on nuances of people not speaking as opposed to speaking.

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