Arculix Risk Engine
The Brain that Goes Beyond the Binary

Continuous Authentication Technology with Real-Time Threat Analytics and Risk Scores
Arculix’s risk engine is the heart of our technology platform – and with 47 patents – is the strongest and most comprehensive engine.
Leveraging AI / ML, Arculix monitors hundreds of variables to calculate whether an access attempt is legitimate or not by tracking user and device posture pre-authentication, during authentication and post-authorization.


Calculate the Level of Assurance for Each Transaction
Level of Assurance used with intelligent multi-factor authentication decides whether to increase or decrease the friction for the user.
Re-Authentication: Avoiding MFA Fatigue
Leverage behavioral analytics and environmental context to simplify policies. Security authenticators define normal behavioral patterns for the user so fewer threat checks need to be defined.
After initial authentication, these measures will be used on a continuous basis to reevaluate the user’s behavior to determine if there has been enough change to warrant a re-authentication request.

Re-Authentication When Users Engages in Higher-Risk Activities
Workforce Identity
An employee could be called upon to reauthenticate if something changes in their behavior (i.e., they suddenly leave the building with their phone, laptop or other personal devices).
Customer Identity
A customer can shop online all day but must authenticate their identity once they purchase any of the items in their shopping cart.
Analytics Drive Better Security and Identity Protection
Machine Learning Risk Engine
Use machine learning powered technology to assess user login risk and user profile risk from built-in and external signaling services.
Extensible 3rd party Signaling
Connect to your existing threat intelligence solutions such as PAM, SIEM, IGA, and UEBA to enhance risk analysis and improve your security posture with even stronger risk scoring.
Contextual and Behavioral Signals
Continuously feeds dozens of contextual and behavioral signals such as user location, user device, login velocity, browsers, cell phone network or ISP into the user profile engine to maintain an accurate user behavior profile.
Dynamic Risk Score
Based on a risk score computed by our proprietary AI/ML algorithms, a dynamic level of assurance (LoA) is computed.
Our approach automatically finds the optimal policy for each transaction to maximize security while minimizing friction for the user with machine learning and AI analytics.
This provides a smoother user experience without sacrificing secure authentication.
