Category: aiSIEM

Automated Threat Detection and Response

Automated Threat Detection and Response

The modern digital economy exposes organizations to cyber threats that are more frequent, sophisticated, and damaging than ever before. From ransomware campaigns and insider attacks to advanced persistent threats, the cybersecurity landscape has grown increasingly complex, leaving businesses vulnerable. While traditional security solutions still play a role, they are often reactive and fragmented, creating exploitable

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Machine Learning Security Platform

Machine Learning Security Platform

In today’s rapidly evolving digital landscape, cyber threats are no longer static or predictable. From advanced persistent threats (APTs) and insider risks to ransomware and zero-day exploits, attackers are becoming more sophisticated every day. Traditional security tools that rely heavily on predefined rules or signature-based detection often fail to stop these dynamic and stealthy attacks.

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Behavioral Analytics

Behavioral Analytics

The cybersecurity threat landscape has evolved beyond recognition over the past decade. Traditional security tools that relied heavily on signature-based detection are no longer sufficient to counter the sophisticated, multi-vector attacks of modern cybercriminals. Threat actors are constantly adapting, exploiting zero-day vulnerabilities, using stolen credentials, and deploying advanced tactics to evade detection. This is where

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IoT Security

IoT Security

As the Internet of Things (IoT) continues to transform industries and daily lives, security has become one of the most critical challenges organizations face. From smart homes and connected cars to industrial systems and healthcare devices, IoT ecosystems are vast and deeply integrated into business operations and personal environments. However, with this rapid adoption comes

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