Cybersecurity Threat Detection
AI-driven threat detection and response system for enterprise security.
The Problem
A critical national infrastructure operator was experiencing advanced persistent threat (APT) intrusions that bypassed their signature-based SIEM, resulting in two data exfiltration incidents. Threat analysts were drowning in 400,000+ daily alerts with a 0.1% signal-to-noise ratio.
Our Approach
We built a behavioural AI threat detection platform using unsupervised anomaly detection on network flow data, trained on 18 months of baseline activity. Entity correlation graphs built in Neo4j identify lateral movement patterns invisible to rule-based systems. Alert triage is automated through an LLM-powered analyst assistant that drafts incident reports.
Measured Results
- 99.3%Alert Noise Reduced
- 4.2minMean Detection Time
- 0Breaches Since Deploy
- 400K+Daily Events Processed
Want Results Like These?
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