EGRESS PREVENT

Contextual machine learning

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Contextual machine learning

We use artificial intelligence and machine learning to understand users' behaviour in real time. This includes the context of who they communicate with and where they are located, the time they're communicating with these recipients, and the content contained within each email's body and attachments. 

We can then dynamically detect any abnormal behaviour when employees either make mistakes or intentionally leak data.

Features Prevent Contextualml Behaviour

Continuously understanding users' behavior

Bayesian inference models continuously update our risk assessments as more information about user roles becomes available, dynamically preventing emails being sent to the wrong person or with the wrong files attached.

Features Prevent Contextualml Relationship

Assessing relationship strength

We deploy graph databases to map out and interrogate the strength of a user's relationships in order to detect anomalous recipients and prevent misdirected emails.

Features Prevent Contextualml Timegraph

Monitoring time patterns

Gaussian mixture models allow Egress Prevent to continuously learn about users' access time patterns, meaning we can spot unusual behavior and stop email data breaches.

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