VIBRE

VIBRE operates at the intersection of neuroscience, workplace safety, wearables, and data analytics. Its Neuroframe system is described as combining a wearable forehead sensor with software that analyzes brain data, rather than relying only on self-reported fatigue or general workplace observations. The stated use cases include assessing attention, drowsiness, mental fatigue, and workload during high-concentration activities, with options for real-time monitoring and retrospective, step-by-step work-process analysis. VIBRE also describes anonymized group reporting to surface anomalies and potential process risk points. This positions the company around occupational applications of neurotechnology, with examples spanning wind farm maintenance, interventional cardiology, and Formula 1 operations. The available company information does not identify named competitors or provide comparative performance, clinical validation, or customer-scale metrics, so a direct competitive ranking is not supportable. Its clearest differentiators are the combination of wearable brain-data collection, work-procedure analysis, and workplace-focused reporting. The company’s recorded pre-seed funding and limited disclosed operating metrics suggest a small-scale profile relative to established workplace-health and sensing providers.

VIBRE was founded in 2018 and announced one pre-seed round on Apr 1, 2018: €101,000, equivalent to $124,364. The company’s product, Neuroframe, combines a wearable forehead sensor with software and neuroscience-informed algorithms intended to assess attention, fatigue, and drowsiness. The available employee-size indicator places VIBRE in the 11–50 range, while a separate position count lists one current role; those figures do not align and should be treated cautiously. No hiring news, recent product launches, or subsequent financing are documented here. Overall, the available indicators point to an early-stage company whose growth case depends on translating its wearable neurotechnology and process-analysis approach into repeatable workplace deployments, but the information provided is not sufficient to assess commercial momentum or adoption.