Plurilock provides invisible multi-factor authentication and continuous user verification through behavioral biometrics and machine learning algorithms. This technology mitigates the risk of unauthorized access by accurately identifying users based on their unique interaction patterns with devices, enhancing security without disrupting user experience.
Funding
$665.5K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional multi-factor authentication methods can be disruptive to user workflows, while also remaining vulnerable to sophisticated attacks such as phishing and credential compromise. This creates a need for continuous authentication solutions that can verify user identity without impacting productivity.
Solution
Plurilock offers an AI-driven continuous authentication platform that verifies user identity in real-time based on behavioral biometrics. The platform uses machine learning algorithms to analyze a user's unique interaction patterns with their devices, such as typing rhythm and mouse movements. By continuously monitoring these patterns, Plurilock can detect anomalies and prevent unauthorized access without requiring users to take any additional steps. This approach enhances security while maintaining a frictionless user experience, addressing the limitations of traditional authentication methods. Plurilock's technology also extends to data loss prevention, providing control over data flow within an organization to prevent unauthorized downloading, uploading, or sharing of sensitive information.
Target Audience
Plurilock's primary customers include enterprises, government agencies, and organizations in regulated industries seeking to enhance their cybersecurity posture and comply with data protection regulations.
Features
- Continuous authentication through behavioral biometrics and machine learning
- Real-time user verification based on unique interaction patterns
- Adaptive risk scoring to dynamically adjust security measures
- Data Loss Prevention (DLP) capabilities to control data flow
- Passwordless Single Sign-On (SSO) and Multi-Factor Authentication (MFA)
- Integration with existing security infrastructure and identity management systems
- AI-driven analysis of user behavior to identify potential insider threats
- Endpoint data security and personal account blocks