Start with the threat.
End with a defended host.
Ransomware on a third-party supplier. An APT hiding behind container traffic. NIS2 reporting in 24 hours. A hijacked roadside camera. A shadow AI agent exfiltrating credentials. Each is a different story — and each lands the same way: at the runtime layer of a host, where AI EdgeLabs sees and stops it before damage occurs.
Turn NIS2 and CRA from a risk into a competitive advantage.
NIS2 entered into force in October 2024. CRA applies to all connected products from 2027 — with enforceable fines up to 2–2.5% of global turnover. Both shift accountability upward to the management body and demand continuous, exportable evidence of runtime control. AI EdgeLabs is built to deliver exactly that.
NIS2 Directive — essential & important entities
Continuous risk management, runtime threat detection, supply-chain monitoring, and 24-hour incident reporting are now binding obligations for energy, transportation, telecom, manufacturing, and digital infrastructure operators. We deliver them in one agent.
- Always-on runtime detection across hosts & edge
- SBOM monitoring & runtime vulnerability handling
- 24h / 72h incident report templates
- Tamper-resistant audit evidence per host
EU Cyber Resilience Act — connected products
Manufacturers of all connected products with digital elements — IoT, industrial controllers, embedded systems, AI-enabled edge components — must ship secure-by-design, maintain a live SBOM, and disclose vulnerabilities within 24 hours. CES marking depends on it from September 2026.
- Continuous SBOM & CVE monitoring per device
- Coordinated disclosure-ready evidence
- Post-market runtime monitoring proof
- Custom OS / firmware SBOM upload supported
One control map, every framework
Security teams under NIS2 and CRA almost always also live with ISO/IEC 27001, ISO/IEC 62443, HIPAA, PCI DSS, FedRAMP, or NIST. The Compliance Center keeps a single posture model and exports framework-specific evidence on demand.
Win regulated contracts faster
Compliance evidence is now a buyer requirement, not just a regulator one. Demonstrate verifiable cyber resilience — auditable logs, AI-assisted runtime defence, automated patching, built-in compliance reporting — to enterprise customers, public-sector buyers, and supply-chain partners.
- One-click executive risk posture report
- Vendor / customer evidence exports
- Continuous proof, not point-in-time snapshots
Stop the attack patterns defining 2025 and 2026.
Modern incidents rarely stay inside one organisation. They propagate through suppliers, service providers, and shared digital infrastructure — often crossing borders within hours. Each card below maps a real attack pattern observed in production to the runtime control that contains it.
Ransomware & supply-chain attacks
Collins Aerospace's MUSE outage (Sep 2025) shut down check-in across Berlin, Brussels, and Heathrow. Jaguar Land Rover lost £485M to a coordinated attack from Scattered Spider, Lapsus$, and ShinyHunters that began with social engineering. Both started with one third-party node.
Nation-state & APT-grade threats
Salt Typhoon moved laterally for three years past every perimeter tool deployed. AI EdgeLabs detection algorithms and response playbooks were forged in real operations against Sandworm, APT28, APT44, NotPetya, Industroyer, and AcidPour — encoded into every agent we ship.
DDoS & service disruption
For telecom carriers, smart cities, and gaming platforms a DDoS event isn't an inconvenience — it's an SLA breach. Inline AI detection neutralises volumetric and behavioural attacks at line rate before service availability is impacted.
Zero-day & novel exploits
Signature-only tools miss what they've never seen. Kernel-level eBPF + behavioural ML detects exploitation patterns regardless of CVE — and AI-generated playbooks contain the threat in seconds while you wait for the vendor patch.
Compromised edge & IoT devices
In 2025, hostile actors used compromised border and logistics CCTV to track aid flows into Ukraine — turning ordinary IP cameras into a battlefield reconnaissance network. SCADA, telematics, and warehouse control increasingly carry the same risk: unmanaged edge devices become low-cost, high-impact entry points.
Insider risk & misconfigurations
Complex orchestration and manual changes routinely open paths to compromise. Continuous host audit and KSPM detect privileged exec, exposed services, RBAC drift, and host-config deviations from your secure baseline — before an auditor or attacker does.
Defend the workloads cloud-only tools can't reach.
AI has lowered the cost of attack and compressed response windows. Cloudflare blocked 416 billion AI bot requests for customers since July 2025 alone — and that is only the volume visible at the edge of their network. Inside enterprises the same automation hits inference pipelines, GPU clusters, and air-gapped sites that legacy stacks were never designed to defend.
AI / LLM agents & shadow AI
A single prompt can instruct an agent to delete files, exfiltrate credentials, or call a compromised package registry — through tool calls your existing stack never sees. Parallax intercepts every tool call, redacts secrets, and blocks dangerous operations before they execute. Shadow AI endpoints are surfaced continuously from host and network telemetry.
GPU cloud / multi-tenant AI
GPUaaS providers face APTs, cryptojacking, and tenant breakout against highly valuable hardware. AI EdgeLabs adds runtime model integrity and agent-level visibility without disrupting AI throughput — keeping high-performance compute secure, reliable, and customer-ready.
Sovereign & air-gapped environments
Government, defence, and regulated cloud workloads cannot ship telemetry out for analysis — and most modern security platforms simply cannot run there. Zero-egress architecture means full inference and response stay on the host, with no cloud dependency and no data leaving the boundary.
Distributed edge at scale
Smart cities, telcos, energy, and transport operators deploy thousands of resource-constrained nodes with intermittent connectivity. A master-node architecture secures 50–500 workloads per agent, scales to thousands of sites in minutes, and consumes up to 300 MB/month of network traffic per node.
SOC acceleration with AI
A two-person security team gets the response capability of a twenty-person SOC. AI Security Assistant translates noisy EDR alerts into clear MITRE-mapped narratives; AI-generated playbooks turn investigation into a one-click action — drop MTTR from hours to milliseconds.
Linux server & container fleets
Linux powers the majority of enterprise workloads — and traditional EDRs were built for Windows endpoints. eBPF-native protection covers every Linux distribution, container runtime, and embedded variant with the same lightweight agent and minimal-interference design.
Bring us the use case. We'll bring the runtime evidence.
Twenty-minute working session: walk through the threat or obligation that brought you here, and we'll map exactly which modules answer it — with reference customers, telemetry, and pilot scope.