Workloads & Application Security

Runtime Protection for Hybrid, Edge & AI-Driven Infrastructure

Built for Distributed, Regulated, and Offline Environments

AI EdgeLabs protects modern workloads end-to-end, without architectural changes or cloud dependency, so security stays enforced everywhere you run.

Hybrid Cloud & Datacenters

Protect VMs and hosts across private and public infrastructure.

Kubernetes & Containers

Secure containerized workloads and Kubernetes runtime operations.

Distributed Edge Environments

Defend multi-site edge deployments on resource-restricted devices.

Offline / Air-Gapped Operations

Enforce protection without connectivity or cloud dependency.

Hypervisor & Bare-Metal VMs

Extend runtime security to hypervisor layers and bare-metal hosts.

GPU / AI Workloads

Secure performance-sensitive GPU systems without disrupting AI throughput.

Runtime Protection, Automated Response, Continuous Compliance

Runtime Protection

Monitors networks, processes, software, and exposures for real-time runtime visibility.

eBPF System Telemetry

Captures system-call signals for high-fidelity detection beyond logs and blind spots.

Network Threat Prevention

Detects attacks and auto-blocks traffic to stop flooding, spoofing, and exploitation.

Kubernetes Runtime Protection

Detects risky exec, privileged containers, hostPath mounts, and account abuse.

Response Automation

Executes kill, deny, isolate, block, and quarantine actions using guided playbooks.

Vulnerability & Image Scanning

Identifies CVEs and package/base-image risk across images and VMs.

Misconfiguration & Host Audit

Finds host/K8s misconfigs and enforces least privilege via continuous auditing.

Continuous Compliance & Auditing

Generates benchmarks, evidence, timelines, and reports for ongoing audit readiness.

See Your Risks Before Attackers Do

Meet with our experts and experience how AI-native runtime security defends applications, containers, APIs, and AI workloads across hybrid environments.