Extended AI-Native
Runtime Security Platform

Unified runtime detection and response across every workload and AI agent — hybrid cloud, Kubernetes, sovereign, air-gapped, and GPU environments. Deploy a single container per host for full-stack visibility from kernel to application layer. All inference runs locally. Zero data egress.

<1ms
Detection latency
1container
Full runtime coverage
<4% CPU
Per-node overhead
0egress
Inference stays local
Network Inspect every packet, in & out of the workload Syscalls eBPF kernel-level visibility into processes WORKLOAD NETWORK BEHAVIOUR SYSCALLS FILE I/O Behaviour ML baselines spot drift from normal File I/O Guard secrets & data at rest
The problem

Securing AI requires a totally new approach

Threats are no longer human-speed. Your stack is. The runtime layer — where every modern attack actually executes — is the one place legacy security tooling can't see. Attackers weaponise AI to discover, exploit, and exfiltrate in seconds. The only way to match that speed is autonomous detection and response at the point of execution.

Problem 01

Attackers operate at machine speed

Autonomous, AI-driven exploitation completes in seconds — from initial access to lateral movement and exfiltration. By the time a SIEM correlates an alert, the attacker has already achieved their objective. Human-speed triage, manual runbooks, and ticket-based workflows are no longer competitive against adversaries that move at machine speed.

Problem 02

Existing tools are blind to the host

Perimeter, CNAPP, EDR, and SIEM stacks see the boundary, the cloud posture, or the laptop — none of them see what is executing inside containers and AI workloads in real time. Salt Typhoon moved laterally for three years past every perimeter tool deployed. The runtime layer is the critical gap in the modern security stack, and it's where attackers live.

Problem 03

Cloud-dependent security can't go everywhere

Sovereign, air-gapped, defence, and edge deployments can't ship telemetry out for analysis. Most modern security platforms simply can't run there — leaving the most regulated and highest-stakes environments with no runtime protection. If your security depends on cloud connectivity, it fails in the environments that need it most.

Killer feature

Stop attacks in sub-milliseconds — before they execute

Detection without response is just expensive logging.

EdgeLabs runs on the host. Every runtime detection and response happens at the point of execution — no cloud round-trip, no waiting for remote analysis. The agent intercepts malicious activity at the syscall level, correlates across process, network, and file layers, and responds autonomously before the attack completes. Every alert is backed by full execution context and evidence, not noise.

Sub-millisecond response. Zero cloud dependency. Signal that actually means something.

AI EdgeLabs runtime alert with AI-generated playbook
Where it runs

One deployment. Full runtime coverage everywhere your workloads run.

A single lightweight container deploys unified runtime protection — network, workload, and vulnerability — directly onto every host. All inference runs locally with under 4% CPU overhead per node. Nothing leaves your infrastructure boundary.

Hybrid cloud & data centres

Unified runtime visibility across private and public infrastructure — AWS, Azure, GCP, and on-premise hosts on a single pane of glass. No cloud dependency for detection or response.

Kubernetes & containers

Runtime protection from image to execution. Detect container breakout, fileless malware, lateral movement, and privilege escalation as they happen — not after. Less than 4% CPU overhead per node.

Distributed multi-site infrastructure

Protect workloads across geographically distributed deployments on resource-constrained devices. The full detection and response stack operates without continuous connectivity.

Sovereign & air-gapped environments

Zero data egress architecture — all inference runs locally on the host. Built for government cloud, defence infrastructure, and regulated environments where data cannot leave the boundary. FedRAMP and NIS2 aligned.

Hypervisor & bare-metal

Runtime security extended to the hypervisor layer and bare-metal hosts — protecting the foundation that all your virtualised workloads run on, the layer endpoint tools never see.

GPU & AI workloads

Secure performance-sensitive GPU systems without disrupting AI throughput. Detect model tampering, resource exhaustion, and data exfiltration from inference workloads — at sub-millisecond latency with negligible overhead.

How it works

Protect actively what costs the most.

Five runtime capabilities, one unified agent. From kernel-level visibility to autonomous incident response — all executed locally at the edge, with or without a human in the loop.

01 — Visibility

Deep runtime visibility

See every syscall, process tree, network connection, and file operation — on the host, as it happens. Full execution context from kernel to application layer, before any tool above it knows it occurred.

02 — Signal

High-fidelity signals

Every alert is backed by correlated evidence across process, network, and file layers — so your team receives actionable context, not alert fatigue. Thousands of noisy events distil into the handful of signals that matter.

03 — Response

Autonomous incident response

Autonomous blocking and pre-defined playbooks respond instantly at the agent layer. For novel and APT-class threats, AI trained on real nation-state attack response generates custom executable remediation scripts in seconds. From detection to containment without waiting for a human decision.

04 — Sovereignty

Zero data egress

All inference runs locally on the host. Nothing leaves your infrastructure boundary — ever. Purpose-built for sovereign, air-gapped, and highly regulated environments where cloud dependency is not an option and data residency is non-negotiable.

05 — APT-grade

APT-grade protection

Detection algorithms and response playbooks built from real operational experience responding to Sandworm, APT28, and APT44 — not threat intelligence reports. The institutional knowledge of a decade of nation-state defence, encoded into every agent.

Competition

Traditional security were not built to secure at machine speed.

Your security stack was built for human-speed threats. Attacks are no longer human-speed.

Most existing security solutions were designed for a threat landscape where attackers moved slowly enough for humans to respond. They were not built to detect and contain autonomous AI-driven exploitation that completes in seconds. While each tool remains important for its domain, they share a critical blind spot: none of them see what is executing on the host in real time, and none of them can respond before damage occurs.

Perimeter tools

Firewalls, WAFs, Network Detection

Palo Alto · Fortinet · Cisco

See the boundary. Blind to everything inside. Salt Typhoon spent three years moving laterally past every perimeter tool deployed.

× No host runtime visibility
CNAPPs

Cloud Posture & Vuln

Wiz · Prisma Cloud · Lacework

Excellent cloud posture and vulnerability visibility. Agentless architecture means no runtime depth. Cannot operate in sovereign or air-gapped environments. Blind once the workload is running.

× No runtime depth · cloud-only
EDR / XDR

Endpoint Detection

CrowdStrike · SentinelOne

Strong endpoint coverage. Built for laptops and workstations. Limited runtime depth inside containers and Kubernetes. Cloud-dependent for correlation and response. Not designed for AI agent workloads.

× Not built for AI / containers
SIEMs

Log & Event Correlation

Splunk · Microsoft Sentinel · IBM QRadar

Collect and correlate after the fact. Investigate history, not the present. MTTR measured in hours or days. Generate high volume, low fidelity signal. Not built for machine-speed threats.

× Post-incident, human-speed
AI EdgeLabs

AI-Native Runtime Security

Hosts · Containers · GPU · Sovereign · Air-Gapped

Sub-millisecond detection and response on the host, before damage occurs. Operates fully offline. APT-grade response built from real operational experience against Sandworm, APT28, and APT44. AI agent and GPU workloads protected natively.

✓ See and stop on the host, in real time
Outcomes

What changes when threats stop completing.

When security operates at the speed of the attack — on the host, before damage occurs — the operational metrics your organisation tracks look fundamentally different. Here's what changes.

hours → ms

MTTR drops from hours to milliseconds

Mean time to respond stops being a KPI your team struggles to improve quarter after quarter. Autonomous response at the agent layer contains threats before your analyst reads the first alert — turning incident response from a reactive scramble into an automated guarantee.

5,000 → 5

Alert volume drops. Signal quality rises.

Full execution context eliminates false positives at the source. Your SOC works through five alerts that matter — not five thousand that don't. Analysts spend time investigating real threats instead of triaging noise.

Continuous

Compliance becomes continuous, not periodic

Tamper-resistant audit trails, runtime evidence, and pre-built framework mappings mean audit readiness is a default state — not a quarterly scramble. CRA, NIS2, HIPAA, FedRAMP covered out of the box.

−2 to −3 tools

Security costs consolidate

One runtime platform replaces multiple point solutions — perimeter tools, container scanners, SIEM noise reduction layers. Organisations with mature stacks typically eliminate two to three redundant tools within the first six months of deployment.

Air-gap ✓

Sovereign deployments become possible

Zero data egress architecture means environments that could not previously deploy cloud-dependent security now have full runtime protection. Air-gapped, government, defence, and regulated deployments are supported natively without compromise.

2 = 20

Small teams, APT-grade capability

AI-generated executable playbooks give a two-person security team the response capability of a twenty-person SOC. A decade of nation-state attack response knowledge — available on demand and executable in seconds.

Validation

Built in the most targeted threat environment on earth.

Our team has Ukrainian roots and operated on the most targeted cyber infrastructure on earth for over a decade — responding directly to Sandworm, APT28, APT44, NotPetya, Industroyer, and AcidPour. Every detection model and response playbook in the platform was forged in real-world operations against the most capable adversaries on the planet.

AI EdgeLabs is not built from threat intelligence reports. It is built from operational experience in the most dreadful cyberwarfare — and that experience is encoded into every agent we ship.

Sandworm APT28 APT44 NotPetya Industroyer AcidPour
Fortune 500
Enterprise deployment
Case study
Rekor
Telecom
Major Telco Provider
Defence
Defence Project

See exactly what's executing on your hosts — in real time.

Deploy a single container per host. Get full runtime visibility in minutes. Block your first attack in sub-milliseconds — no cloud dependency, no data egress.