RAD Security

Ingest raw alert streams from connected SIEM and EDR tools.

Pass alerts through the Noise to Focus engine for initial anomaly filtering.

AI Workers analyze remaining alerts against current threat intelligence.

Escalate only high-fidelity, verified alerts to the human analyst dashboard.

A critical alert triggers the creation of a new Evidence Room.

AI Workers automatically populate the room with relevant logs, user identities, and endpoint telemetry.

Security analysts join the Evidence Room workspace to collaborate and share findings.

The team finalizes remediation steps based on the centralized evidence package.

A threat hunter formulates a hypothesis about a potential hidden compromise.

The hunter drafts a highly specific query using RadQL.

The platform executes the RadQL query across the organization's aggregated security data.

Results are visualized in the dashboard, highlighting outliers for further investigation.

Configure and deploy AI Workers with specific 24/7 monitoring parameters.

AI Workers continuously analyze incoming telemetry and network traffic.

Upon detecting an anomaly, the AI Worker performs an automated initial investigation.

The system generates a preliminary report and alerts the on-call engineer if human intervention is required.

Access the Platform Bento dashboard for aggregated metrics.

Review data on the ratio of noise filtered versus critical alerts escalated.

Analyze the performance and case resolution rates of deployed AI Workers.

Export a comprehensive, visually rich summary report for stakeholder meetings.