imper.ai Impersonation Detection Platform analyzes forensic markers to detect and prevent impersonation and social engineering attacks across communication channels. The platform examines device fingerprints, network intelligence, and digital identity signals to identify suspicious activity in real-time. The detection engine correlates hundreds of security signals including IP geolocation mismatches, VPN usage, network layout, device telemetry, virtual machine detection, browser analysis, usage patterns, and cross-channel consistency. These signals are benchmarked against expected patterns to reveal anomalies that indicate manipulated or fake identities. The platform assigns real-time risk scores to every user interaction based on policy-based thresholds. When risk scores exceed acceptable levels, automated workflows can allow, restrict, or block sessions instantly. Real-time alerts notify staff when impersonation attempts are detected, enabling immediate action. Verification workflows can be initiated via chat, email, or embedded into collaboration tools and help desk systems. The platform processes only metadata without storing content, credentials, or sensitive data. No agents or installs are required for deployment. The platform is SOC 2 Type II certified and compliant with GDPR and CCPA regulations. It provides channel-agnostic verification with native integrations and APIs for collaboration, support, and communication platforms.