Data-Driven Workplace Well-Being
Imagine a system that isn't just a static survey, but a dynamic, continuously learning tool that helps employees feel better and gives leadership a real-time view into productivity, job satisfaction, and sick leave. Trend data and AI-powered recommendations enable timely action and prevent issues before they escalate.
We are developing a completely new kind of occupational well-being system that replaces static annual surveys with a dynamic, continuously learning tool. This system helps employees feel better and gives leadership real-time insight into the organization's well-being, efficiency, and trends in sick leave. It enables early intervention — before issues grow large enough to impact company performance. With constantly updating trend data and recommendations, there's no need to wait — you can act now.
Our system acts as a reflective, conversational interviewer that adapts its communication style. It helps identify the aspects of an employee's well-being that need attention. It adjusts to each user's language, education level, and needs, asks questions with empathy and a solution-focused tone, and ensures that employees feel heard. The system draws out essential information respectfully and analyzes responses to highlight both individual needs and company-wide patterns.
Every employee gets their own personalized "bot," which adapts to their language, background, and needs. This bot engages in empathetic, solution-focused conversations to uncover well-being challenges and provide individual recommendations.
On the organizational level, all individual bots are linked to a central company analytics bot, which aggregates anonymized data and provides leadership with clear, real-time trend insights. This enables early detection and prevention of problem areas — before they manifest as sick leave or productivity losses.
The system creates a personal bot for each employee, which continuously learns from the user. This bot adapts to language, education level, and individual needs. It communicates empathetically and reflectively, identifies well-being challenges, and offers personalized recommendations. Interaction is solution-focused, ensuring the employee truly feels heard.
The analytics bot acts as an analyst and 'maintainer' for personal bots. It aggregates anonymized data from individual responses and generates valid trend information. The system adjusts predefined parameters to each employee's needs, measures different things for different people, and provides targeted recommendations.
The system reduces sick leave and improves employee well-being. This translates into cost savings (10–20% fewer absences) and increased productivity. Real-time data enables quick response to problems before they escalate.
The system continuously collects and analyzes employee well-being data, offering personal guidance and coaching. For management, it produces real-time trends and recommendations to support effective and proactive action.
Traditional surveys are static and rarely conducted. This system is dynamic and continuously updated, enabling real-time employee support without long delays for results.
The first trends are visible within 2–3 months. Within six months, a comprehensive picture emerges of the system's impact on well-being and sick leave.
During the pilot phase, deployment includes development updates and support. After launch, the system is fully ready and easy to implement thanks to its cloud-based design.
Personal data is anonymized. Management sees only aggregated trend data. All information is processed according to GDPR and other data protection regulations.
Pricing is tied to achieved savings or offered as a licensing model. Final pricing will be published during 2025. A fair and transparent model will be applied.
The system enables continuous interaction at the individual level and provides leadership with trend data across the organization. This helps identify issues early and supports a more unified culture.
The system gives employees suggestions for balancing work and personal life. Management can monitor trends and detect broader issues if they arise.
Predictive analytics identifies at-risk groups and helps target interventions effectively. Personalized support increases engagement and reduces turnover.
Recommendations are adapted to employees' backgrounds and resources. For lower-income roles, affordable options are prioritized, while specialists receive more in-depth guidance.
The system is multilingual and flexibly adaptable to different cultures. Recommendations are tailored to local needs.
Communication adapts to the organization's needs, using methods like text messages or multimedia channels to improve engagement.
The system connects easily to other platforms via REST and WebSocket interfaces, enabling seamless operation with HR, health, and production systems.
The system learns from employee responses and behavior, offering personalized recommendations and support tailored to each individual's needs.
Integration with other systems is smooth, ensuring wide compatibility and reliable operation within the organization's ecosystem.