REMI is trained to recognize the behaviors behind advanced adversarial cyber attacks, not just isolated alerts or known malware signatures. It analyzes event logs, endpoint activity, identity records, VPN sessions, firewall traffic, file activity, commands, scripts, system changes, and operational records to identify how an attack is unfolding across the evidence.

REMI looks for behavior patterns associated with state-sponsored and advanced persistent threat activity, including quiet access, credential misuse, living-off-the-land commands, remote access abuse, lateral movement, tool staging, persistence, data access, configuration changes, and pre-positioning inside critical infrastructure networks. These are the kinds of patterns seen in advanced campaigns, including Volt Typhoon-style activity, where the concern is not always immediate destruction, but stealthy movement, access maintenance, and positioning inside important systems.

Instead of relying on one alert to explain the incident, REMI connects the records that belong together and reconstructs the activity into a clear forensic story: how access was achieved, which systems were touched, what changed, what evidence supports the finding, what remains unresolved, and what responders should do next.

Once REMI Shows You What AI Can Do, You’re Going to Love It. I Guarantee It.