TECHNOLOGY

Employee engagement enhanced by technology

We are shaping the future of employee engagement with new technology and support from the ZHAW & Innosuisse.

Advanced engagement with AI

We know that one-size-fits-all solutions do not exist. To meet all customer-specific requirements, we have developed algorithms that support you in creating customized surveys and a unique employee experience. Machine learning is implemented to process employees' specific answers to questions, ensuring that surveys are individualized and preventing survey fatigue. The activities then suggested to employees as measures are tailored based on their interests and needs.

Logic tree for optimizing surveys

Our logic tree is a core feature of our survey methodology. It comprises an extensive catalogue of questions on employee engagement and the overall employee life cycle. Its technology is implemented to generate individualized follow-up questions based on the answers given, so no two surveys are ever the same.

NLP Sentiment analysis

Survey answers from numerical rating scales can provide accurate feedback. Combining these numbers with sentiment analyses gives even more precise insights. Our natural language processing (NLP) technology enables mood analysis from comments and texts in feedback in German and English. Words are allocated into our predefined categories ranking them on a scale from 1-5, enabling the analysis of combined survey styles for precise results.

Integrable…or stand-alone solution

Our modules can be seamlessly integrated into your intranet or HCM system with APIs. We maintain standardized APIs for common software solutions or create new ones as needed. If your organization is missing a complete intranet, we are here to equip you with the optimal tool: professional communication, activity management, surveys for all employees atwork.

With hands, head and heart atwork.

Discover how to increase engagement atwork. Let us guide you through a product demo of our modules and provide you with customized pricing.