Observe
Monitor detections, AI traces, and policy violations without automation.
Platform Overview
Security telemetry, policy decisions, AI runtime traces, and evidence all operate on the same graph.
CyberPerimeter is built as a policy-driven operating layer for enterprises that need to observe, govern, and respond across both traditional infrastructure and AI-native systems.
Core Design Principles
- Policy before autonomy: every action is checked against approval policies, blast-radius rules, separation-of-duties, and rollback capability.
- Trace every model and tool boundary: prompts, tool calls, retrieval events, policy decisions, validations, and approvals stay visible.
- Treat AI assets as first-class assets: models, agents, tools, evaluators, and datasets are governed alongside users and workloads.
- High-risk actions require human approval: sensitive or irreversible actions route through workflows instead of blind execution.
- Evidence is a product feature: controls, exceptions, and remediation histories continuously produce defensible audit trails.
Operational Modes
Recommend
Generate response options, owners, and likely blast radius before action.
Guarded Execute
Automate bounded actions with preview, policy checks, and rollback plans.
Approval-Gated
Escalate higher-risk actions to humans with full context and evidence attached.
Workspaces
Purpose-built views for the teams that need to act.
Command Center
Incidents, detections, risk queues, and response workflow status for security operations.
AI Runtime Explorer
Tracing, tool graphs, groundedness analysis, model behavior, and runtime anomalies for AI platform teams.
Policy Studio
Playbooks, approvals, blast-radius rules, rollback design, and tool governance for controlled automation.
Compliance Cockpit
Control status, evidence completeness, exceptions, governance registers, and audit package generation.
Continuous Evidence
Every approval, control decision, remediation, and exception contributes to readiness.
The platform turns operational activity into an evidence trail instead of asking teams to reconstruct the past. That lowers audit preparation cost and shortens the distance between incident response and governance review.