Darktrace uses self-learning AI to detect previously unknown threats in network traffic and endpoints without relying on threat signatures. Its patented Enterprise Immune System autonomously responds to emerging cyber-attacks in milliseconds, reducing human intervention.
Fortinet embeds AI across its security fabric to detect and block advanced threats at network, edge, and endpoint layers. The FortiAI engine analyses billions of events to identify threats whilst maintaining network performance.
CrowdStrike Falcon uses lightweight sensors and AI-powered analytics to detect and respond to endpoint threats. Its cloud-native platform scales globally and integrates threat intelligence from millions of monitored systems.
Cortex consolidates security data across endpoints, networks, and cloud environments into a unified AI-powered platform. Its machine learning models automate threat investigation, reducing alert fatigue and investigation time.
Microsoft Defender leverages signals from billions of devices and AI models trained across Microsoft's security research to detect endpoint threats. Integrates natively with Windows and Microsoft 365 environments.
SentinelOne Singularity employs behavioural AI to detect and autonomously remediate endpoint threats. Its patentless technology operates without relying on signature databases, enabling detection of polymorphic and zero-day attacks.
Cisco Talos operates one of the world's largest security research organisations, feeding AI-driven threat intelligence into email, network, and endpoint products. Its machine learning models analyse billions of emails daily to block advanced phishing and malware.
Google Cloud's security operations platform combines SIEM, SOAR, and XDR capabilities with AI models trained on Google's own security data. Provides threat detection and automated response across cloud, on-premise, and multi-cloud workloads.
Rapid7 InsightIDR provides AI-powered threat detection, investigation, and response across logs, endpoints, and network data. Its managed detection and response (MDR) services supplement automated threat detection with human expertise.
Sumo Logic Security provides cloud-native threat detection, cloud security posture management, and investigation capabilities powered by machine learning. Its models continuously learn from customer and industry threat data.
Positions 1, 2 and 3 are available to buy for twelve months. Everyone below moves down a place, and the bottom entry comes off.
Traditional signature-based security relies on known malware patterns and indicators; it cannot detect zero-day exploits or novel variants. AI-powered systems use machine learning to identify anomalous behaviour and previously unseen attack patterns by analysing contextual data, making them effective against emerging threats without waiting for signature updates.
Gradual integration is typically recommended. Most enterprises deploy AI tools to augment existing security infrastructure, starting with high-impact areas like endpoint detection or email security. Full replacement requires careful planning, data migration, and validation to ensure detection capabilities match or exceed current performance before decommissioning legacy tools.
Costs vary widely based on deployment scale and features. Entry-level cloud-native platforms start around $30,000-50,000 annually for small deployments, whilst enterprise-grade solutions from Darktrace, Fortinet, or CrowdStrike often cost $500,000 to several million pounds annually depending on endpoint count, threat intelligence scope, and managed services included.