Autonomous Threat Detection & Response

AI models continuously analyze flow records, packet payloads, and DNS patterns to detect malware, DDoS, and insider threats. Automated response engines isolate infected segments or quarantine compromised devices in real time.

Zero-Trust Microsegmentation

We enforce identity-based segmentation across users, workloads, and IoT devices. Policies are dynamically applied using AI-driven context awareness, ensuring lateral movement is eliminated.

Intent-Based Network Security Policies

Our systems convert high-level business intents into network security policies. Using policy engines, routing and firewall rules are automatically updated to align with compliance and SLA requirements.

Encrypted Traffic Analytics

AI-driven models detect anomalies in encrypted flows without decryption by leveraging metadata features (TLS fingerprints, flow duration, packet sizes), ensuring privacy-preserving security.

QoS-Aware Traffic Optimization

We combine threat detection with QoS enforcement, ensuring critical applications receive guaranteed bandwidth while malicious or non-priority traffic is throttled or dropped.

Unified Hybrid & Multi-Cloud Security

Our solutions extend secure networking across AWS, Azure, and GCP, providing centralized visibility, adaptive firewalls, and AI-driven routing across cloud fabrics.