Stealth provides an AI-driven platform that continuously monitors network traffic, endpoint behavior, and external threat feeds to detect anomalous activity in real time. The system correlates internal telemetry with threat intelligence, generates risk‑scored alerts, and integrates with SIEM/SOAR tools for automated response, giving security teams a unified dashboard to prioritize and remediate incidents quickly.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations lack an efficient way to detect and respond to emerging cyber threats in real time, leading to delayed mitigation and increased risk of data breaches.
Solution
Stealth offers an AI-driven threat detection platform that continuously monitors network traffic, endpoint behavior, and external threat intelligence feeds. By applying machine-learning models to identify anomalous patterns, the system generates actionable alerts for security teams. Integration with existing security information and event management (SIEM) tools enables automated response workflows, reducing the time from detection to remediation. The platform provides a unified dashboard that visualizes threat vectors, risk scores, and remediation status, helping organizations prioritize incidents and improve overall security posture.
Target Audience
Primary customers are mid-sized to large enterprises and managed security service providers that need continuous, automated threat detection across complex IT environments.
Features
- Real-time analysis of network and endpoint data using proprietary machine-learning algorithms
- Correlation of internal telemetry with external threat intelligence sources
- Automated alerting and playbook-driven response integration with major SIEM and SOAR solutions
- Centralized dashboard with risk scoring, incident timelines, and remediation tracking
- API access for custom integrations and data export