Getcontact positions itself as a comprehensive solution for combating unwanted communications, leveraging artificial intelligence and community feedback to identify and block spam calls and messages. The Android application serves as both a caller identification system and proactive protection layer, operating globally to filter out telemarketers, fraud attempts, and robocalls before they reach users' devices. The core functionality revolves around real-time caller identification, where incoming calls are cross-referenced against Getcontact's extensive database of reported numbers. The AI-driven spam detection system analyzes calling patterns and user reports to identify potential threats, automatically blocking known spam numbers while allowing legitimate calls through. The application also functions as a replacement dialer and messaging interface, providing integrated protection across communication channels with customizable blocking settings and whitelist management. User experience varies depending on device configuration, with the interface offering straightforward spam management but potentially significant system resource consumption when set as default communication handler. Real-world usage patterns suggest the application performs optimally as a secondary screening tool rather than primary dialer, particularly given performance concerns noted in user feedback. The design follows utilitarian principles with clear spam alerts and simple toggle controls for blocking categories. User feedback indicates generally positive experiences with call identification accuracy, though technical issues emerge prominently. Mario Ray Mahardhika's August 19, 2025 review documents significant CPU overheating when using Getcontact as default dialer, noting 100% CPU utilization through root shell monitoring. Simultaneously, reviews like Lovely Sharma's August 16, 2025 endorsement praise the authenticity of caller identification, while Mohamed Arafa's August 21, 2025 feedback highlights subscription payment method limitations that affect accessibility. The application demonstrates effective spam blocking capabilities and valuable crowd-sourced caller identification, particularly for users receiving high volumes of unknown calls. However, performance optimization issues and resource consumption concerns present significant limitations, especially for devices with limited processing power. Subscription payment flexibility also appears constrained based on user reports. Ideal use cases involve secondary spam screening rather than primary dialer replacement, with most value derived from its identification database rather than continuous background operation.