About Us

Current intrusion detection and prevention systems (IDS/IPS) rely heavily on static signatures and heuristics. These approaches struggle to keep up with polymorphic and zero-day attacks, produce high false positive rates, and lack adaptability in complex cloud-native and IoT-driven networks.

Cybersecurity threats are increasingly automated and AI-driven, requiring equally adaptive defense systems.

We research and develop intelligent systems powered by artificial intelligence (AI) and machine learning (ML) to proactively detect and mitigate cybersecurity threats. Unlike traditional static defenses, our systems will continuously learn network behavior, adapt to new attack vectors, and distinguish legitimate requests from malicious attempts in real time.