Continuous Identity Verification 

Account takeover is one of the most common and costly threats, ranking among the top causes of breaches and driving and billions in annual losses. Enterprises struggle to defend against it because enforcing high-assurance IDV across tens of thousands of users is complex and inconsistent. Traditional IDV relies on static rules or one-time checks, which attackers easily bypass through phishing, deepfakes, and social engineering attacks on Help Desks. 

TOTAL replaces this brittle approach with Continuous Identity Verification powered by advanced machine learning techniques. The platform builds adaptive identity profiles for every user, learning access patterns across devices, sessions, and environments. These profiles evolve with each interaction, allowing the system to distinguish normal variability from subtle signs of compromise. By correlating signals across digital, physical, and behavioral domains, TOTAL delivers continuous protection against Account Takeover at enterprise scale and without adding friction for legitimate users. 

Key Differentiators 

Unified Identity Detection: Correlates behavioral, network, and device signals across all TOTAL modules to expose threats that bypass point-in-time authentication. 

Contextual Identity Modeling: Builds individualized baselines from device posture and system activity, calibrated to each user’s access patterns and risk exposure. 

Probabilistic Risk Engine: Replaces static rules with advanced scoring models that filter noise, prioritize high-risk events, and trigger automated responses. 

Enterprise Scalability: Designed to enforce strong identity verification seamlessly across tens of thousands of users, devices, and sessions. 

Privacy Controls: Granular options for data collection, processing, and residency ensure alignment with enterprise policies and compliance requirements. 

Real Account Takeover Prevention