Detect DDoS attacks and network anomalies in seconds using adaptive AI trained on real traffic patterns — without drowning your team in false positives.
Modern attacks are faster, more sophisticated, and harder to detect with legacy tools. Your team is fighting blind.
Volumetric, protocol, and application-layer attacks mutate daily. Static rules can't keep up. Your perimeter is always one step behind.
Signature-based detection fails against zero-days, slow exfiltration, and lateral movement. Attackers already know how to evade your SIEM.
Alert fatigue is real. When everything triggers, nothing gets investigated. Critical threats hide in noise while your analysts burn out.
SOCElements learns your network's normal behavior and flags deviations with surgical precision — giving your SOC team context-rich alerts that matter.
Threats identified. From packet capture to SOC alert — no lag, no batch processing.
Models that learn your specific network topology and traffic patterns. What's normal for you isn't normal for everyone.
Every alert includes full context: source, target, attack type, severity, and recommended mitigation steps.
Collect network flows and raw packets from your existing infrastructure. No rerouting, no agents on endpoints.
Advanced ML models analyze behavioral patterns in real-time, comparing against your network's learned baseline.
DDoS, exfiltration, lateral movement, and botnet traffic identified instantly with context and confidence scores.
Actionable alerts delivered directly to your security tools via webhook, API, or native integrations.
Volumetric, protocol and application-layer attacks. Detect amplification, reflection, and slow-rate variants.
Command & control communications, beaconing patterns, and coordinated attack infrastructure fingerprinting.
Slow exfiltration, DNS tunneling, and covert channel detection even with encrypted traffic analysis.
Internal reconnaissance, pass-the-hash, and pivot attempts detected across your east-west traffic.
Built from the ground up with modern machine learning — not ML bolted onto legacy rule engines. Each model learns the baseline of your own network instead of relying on generic signatures.
We tune the baseline with your team during onboarding so alerts reflect what is unusual on your network. Measured results from pilots will be published here once validated.
Built to deploy without rip-and-replace. Integrations with Splunk, Elastic, and cloud providers. No rip-and-replace of your existing stack.
Your traffic never leaves your environment unless you want it to. Deploy on-prem, in your VPC, or as a hybrid configuration.
We are working with a small group of security teams to validate detection quality on real traffic before general release.
Partners get direct access to the engineers, influence over the roadmap, and preferential pricing. In return, we ask for weekly feedback.
We will publish detection rate, precision and latency, with the method used to measure them, as soon as pilots confirm them.
Apply to the programFits directly into your existing security toolchain. No forklift upgrade required.
+ REST API · Webhooks · Custom SIEM connectors
All components follow zero-trust principles. Mutual TLS everywhere, least-privilege access, encrypted at rest and in transit.
Network metadata only — no payload inspection required. Your sensitive data stays in your environment. Designed with GDPR in mind.
Audit logs and role-based access control. We have no security certifications yet; ask us about our current status and roadmap.
Book a 30-minute technical demo with our security engineers. We'll walk through a live attack simulation on a test environment — no slides, just the product.
Join the early access program and help shape the first release. Tell us about your network and we will reply within one business day.