Observe
Telemetry across cloud, identity, SaaS, CI/CD, and AI runtime events.
Unified Security + AI Governance
One control plane for cyber operations, AI runtime protection, and continuous compliance.
CyberPerimeter helps enterprises observe what is happening, decide what is allowed, execute approved actions safely, and prove what occurred with audit-ready evidence.
Control Layers
Reason
Incidents, policy violations, and model behaviors correlated in one graph.
Act
Approval-gated automation with rollback paths and blast-radius controls.
Prove
Continuous evidence collection mapped to controls and audits.
Built for security leaders, AI platform teams, DevSecOps, GRC, and regulated enterprises.
Why CyberPerimeter
Fragmented security tooling cannot govern autonomous systems.
Fragmented operations
Endpoint, cloud, identity, data, and SaaS teams still investigate from disconnected consoles and fragmented evidence.
Unmanaged AI runtime risk
Prompt injection, hallucination, data leakage, vector poisoning, and tool misuse demand runtime controls, not static reviews.
Manual compliance burden
Audit evidence is still assembled after the fact, leaving teams exposed when incidents and regulatory reviews converge.
Platform Pillars
Designed around policy-constrained autonomy.
Unified Asset and AI Inventory
Govern infrastructure, identities, secrets, applications, models, prompts, agents, datasets, and vector stores as first-class assets.
AI Observability Fabric
Capture prompts, tool invocation trees, retrieval lineage, latency, groundedness, policy scoring, and model versions in one timeline.
Runtime Security and Governance
Enforce allowlists, scoped permissions, approval rules, action previews, memory isolation, and MCP inventory controls.
Response Orchestration
Support recommend, guarded execute, approval-gated execution, and tightly bounded automation for low-risk reversible actions.
DevSecOps and AI SDLC
Extend governance into code, dependencies, infrastructure as code, model lineage, datasets, evaluations, and deployment gates.
Continuous Compliance
Map operational activity to control libraries, exceptions, AI governance registers, and auditor-ready reporting continuously.
Reference Architecture
A unified operating layer from telemetry to evidence.
Telemetry and Ingestion Plane
EDR/XDR, IAM, cloud, ticketing, scanners, CI/CD, SaaS, model gateways, vector stores, AI frameworks, and MCP servers.
CyberPerimeter Graph
A live graph of enterprise assets, AI objects, incidents, policies, controls, evidence, exceptions, and remediation actions.
Detection and Reasoning Plane
Traditional cyber detections and AI-specific policy violations are correlated with investigation context and response memory.
Policy and Automation Plane
Decide whether the system should observe, recommend, contain, remediate, hold for approval, or roll back an action.
Evidence and Compliance Plane
Operational events feed evidence packages, attestations, and audit workflows for continuous readiness.
Roadmap
Four workspaces, three delivery phases, one operating model.
Command Center
Phase 1
Unified visibility, core graph, key integrations, playbook runner, evidence store, and basic AI traces.
AI Runtime Explorer
Phase 2
Prompt-injection detection, groundedness evaluation, vector controls, runtime anomalies, and policy-aware approvals.
Policy Studio
Phase 3
Bounded autonomy, response memory, multi-agent policy controls, rollback automation, and continuous assurance maturity.
Compliance Cockpit
Always On
Control status, evidence completeness, exceptions, governance registers, and audit packages for ongoing readiness.
CyberPerimeter secures what enterprises run, what AI systems decide, and what auditors need to prove.
Next Step