Vectra AI

Overview

Vectra AI is a cybersecurity AI leader that delivers an AI-native security and observability platform designed to protect modern networks from modern attacks. The platform sees attackers' every move, connecting the dots across network traffic, identity behavior, and cloud activity. Founded in 2011, Vectra AI helps enterprises reduce cyber risk, detect and contain active threats, and strengthen resilience across hybrid and multi-cloud environments.

At the core of the platform is a set of advanced machine learning capabilities that continuously analyze telemetry from your entire attack surface. It goes beyond simple signature-based detection to identify subtle behavioral anomalies and hidden attack patterns. The AI models learn from real-world attacker tactics, enabling security teams to detect both known and unknown threats with high accuracy and minimal false positives. This AI-driven approach reduces manual investigation time and alert fatigue.

Vectra AI is built for modern IT environments, providing deep visibility and unified threat detection across on-premises, cloud, and hybrid infrastructures. It correlates signals from network, identity, and cloud sources into a single attack narrative, empowering security operations teams to see the full scope of an intrusion and prioritise response actions. The platform integrates seamlessly with existing security tools, automation workflows, and threat intelligence feeds, making it a flexible addition to any security stack.

With Vectra AI, organisations can achieve true cyber-attack resilience. By detecting and responding to threats before they escalate, enterprises can protect critical assets, maintain business continuity, and reduce overall cyber risk. The platform is trusted by security analysts, threat hunters, and CISOs across industries who need a proactive, AI-driven defense against evolving threats.

Core capabilities

AI-Driven Threat Detection

Uses machine learning to identify malicious behavior across network, identity, and cloud.

Network Detection and Response

Continuously monitors network traffic to uncover hidden attacks and lateral movement.

Identity Threat Detection

Analyzes identity behaviors to detect compromised accounts and identity-based intrusions.

Cloud Security Analytics

Provides visibility into cloud activity and detects anomalies across hybrid and multi-cloud environments.

Attack Signal Correlation

Connects related events from multiple attack surfaces into a coherent narrative of the attack.

Adaptive Threat Intelligence

Learns from evolving attacker behaviors to improve detection accuracy and reduce noise.

Automated Response Integrations

Triggers containment actions through existing orchestration and security tools.

Scalable Observability

Delivers centralized visibility across large-scale, distributed network and cloud infrastructures.

Use cases

Detecting advanced persistent threats (APTs)

Investigating identity-based intrusions

Securing hybrid and multi-cloud environments

Prioritized threat hunting across attack surfaces

Reducing alert noise in SOC workflows

Monitoring insider threats and compromised accounts

Achieving cyber resilience for AI-driven enterprises