This is like a smart autopilot for hotel pricing. It watches bookings, market demand, and competitors’ prices, then automatically suggests or sets the best room rates to fill more rooms at higher profit.
Hotels struggle to set the right price for each room on each day across many channels. Manual revenue management is slow, error-prone, and often leaves money on the table or rooms unsold. Lybra RMS automates demand forecasting and pricing decisions to maximize RevPAR and occupancy while reducing manual analysis time.
Domain-specific forecasting models and pricing logic for hospitality, enriched by hotel performance data and market/competitor data, combined with workflow integration into hotel revenue management processes and PMS/channel managers.
Hybrid
Time-Series DB
High (Custom Models/Infra)
Accuracy and latency of large-scale demand forecasting across many hotels and dates, plus integration complexity with PMS and channel managers.
Early Majority
Positioned as an AI-driven, automated revenue management system focused on hotels, likely emphasizing more modern machine learning–based forecasting and user-friendly automation compared with older rule-based RMS tools.