Baby Monitor Saby + Cry Alarm represents a modern approach to infant monitoring by transforming smartphones into a networked surveillance system. Developed by Tapnetic LLC, this iOS application enables parents to monitor children remotely through WiFi, 3G, and LTE connections using two mobile devices—one serving as the monitoring station and the other as the receiver. The app positions itself in the competitive baby monitoring market by emphasizing artificial intelligence capabilities rather than relying solely on traditional audio-level triggers. The application's core functionality centers on its AI-powered recognition system that detects when a child awakens. Unlike conventional monitors that activate based on simple noise thresholds, Saby employs neural networks to distinguish between general household sounds and specific infant vocalizations. This technical approach aims to reduce false alarms while ensuring genuine cries trigger immediate notifications. The system supports both audio and video streaming with adjustable quality settings to accommodate varying network conditions, providing parents with real-time visual access to their child's activities whether the infant is sleeping or playing. User experience revolves around a straightforward interface designed for quick setup and operation. The primary screen displays the live video feed with clear controls for audio activation, night vision toggle, and sensitivity adjustments. Network performance significantly impacts functionality, with stronger connections providing smoother video transmission and faster notification delivery. In practical scenarios, parents can place one device in the nursery while carrying another throughout the home, receiving push notifications with sound alerts when the AI system detects crying. The app maintains background operation but may experience increased battery consumption during extended monitoring sessions. No user reviews are currently available for analysis, making comprehensive assessment of real-world performance challenging. Without verified user feedback, potential buyers lack third-party validation regarding reliability across different home environments, device compatibility issues, or long-term stability. This absence of user testimonials represents a significant gap in evaluating actual performance compared to marketed capabilities. The application demonstrates technological innovation through its neural network implementation, potentially offering more accurate cry detection than threshold-based systems. However, the requirement for two iOS devices represents both a cost consideration and limitation for households without multiple compatible devices. Network dependency introduces another constraint, as unreliable internet connections could compromise monitoring effectiveness. The app appears most suitable for tech-oriented parents seeking flexible monitoring solutions without dedicated hardware, particularly those already possessing multiple iOS devices and stable home networking infrastructure.