From Visibility to Predictive Intelligence
AI LAYER
The AI Layer is a powerful and strategic differentiator in modern DPI solutions. While traditional DPI provides deep packet visibility, the AI Layer unlocks predictive, behavioral, and anomaly-based intelligence, which is essential for threat detection, traffic optimization, and investigative automation - particularly valuable for telcos, LEAs, and government operations.
DPI engines see everything • AI Layers understand it.
Smarter Networks • Faster Decisions • Proactive Defense
Our AI-driven layer turns enriched network metadata into actionable intelligence, enabling more intelligent networks, faster decisions, and proactive defense. By combining anomaly detection, behavioral profiling, protocol fingerprinting, and predictive analytics, Quant Azimuth identifies threats, anticipates trends, and supports targeted interventions across users, devices, and applications.
Anomaly Detection & Behavioral Profiling
• Identifies abnormal traffic behavior at the user, device, or network level, detecting:
◦ Unknown or obfuscated applications.
◦ Encrypted tunneling (e.g., SSH over HTTP, DNS tunneling).
◦ Sudden changes in traffic volume or patterns (e.g., data exfiltration).
Protocol & Application Fingerprinting (ML-Augmented)
• Enhances classification accuracy for encrypted, obfuscated, or zero-day traffic
• Learns and adapts to new apps, VPNs, and evasive protocols over time
• Improves visibility in TLS/SSL traffic using JA3/JA4 fingerprints and behavioral correlation
Threat Detection & Insider Risk Monitoring
• Integrates with SIEM/SOC for alerts and automated triage
• AI-driven detection of:
◦ Malware communication behavior (e.g., C2 beaconing).
◦ Suspicious internal movement (e.g., lateral scanning).
◦ Policy violations or data leakage events.
Predictive Analytics & Forecasting
• Supports proactive network planning and resource allocation
• Analyze historical usage trends to forecast:
◦ Capacity needs.
◦ User behavior evolution.
◦ Potential service degradation.
LEA-Focused Use Cases
• Identify behavioral patterns matching target profiles
• Assist in target re-identification across access types (mobile/fixed/satellite)
• Flag “low-noise” activity such as burner phones or encrypted chat usage
It’s Not Just About Visibility • This Is Intelligent Awareness.
AI Layer in Action
Enriched DPI Metadata
The AI Layer receives enriched DPI metadata (not payloads) from the core engine and database, and applies:
• Supervised ML for known pattern recognition
• Unsupervised ML for anomaly detection (e.g., clustering, PCA)
• Time-series analysis for behavioral trends
• Graph analytics for link analysis (e.g., who talks to whom, how often)
• NLP/NLU for metadata labeling or content-type inference (e.g., HTTP header mining)
Integration & Outputs
• Feeds alerts into:
◦ SIEM/SOC
◦ Case management tools
◦ Control Plane (to trigger policies/actions)
◦ LEA investigation dashboards
• Augments dashboards with:
◦ AI-labeled traffic behaviors
◦ Confidence scores
◦ Risk rankings (user/device/app)
• Optional retraining modules • Custom AI models for national-specific threats or telecom-specific usage patterns
AI Layer Benefits
Anomaly Detection
• Discover threats or evasive behaviors not covered by static rules.
Encrypted Visibility
• Maintain classification even when traffic is encrypted.
Behavioral Intelligence
• Understand how users/devices evolve and deviate.
Network Forecasting
• Proactively address congestion, abuse, or misbehavior.
Automation & Precision
• Reduce analyst workload, increase detection confidence.
Privacy & Governance
The AI Layer transforms the DPI platform into a self-learning, threat-aware, and behavior-intelligent system capable of identifying emerging threats, adapting to changing network behavior, and supporting real-time defense. Operating entirely on metadata, it delivers advanced intelligence without requiring access to payload content, helping organizations maintain strong privacy and regulatory compliance. AI-driven actions and model decisions are fully auditable and explainable, providing the transparency and accountability required for high-assurance environments and making the platform XAI-ready.
