Spectrum automates the full detection lifecycle for security operations, continuously mapping coverage gaps by merging external threat intelligence with internal findings and automatically authoring, tuning, and deploying production‑grade detections across SIEMs, data lakes, and other tools. The platform monitors for drift and breakage, self‑healing detections to maintain effectiveness while reducing alert fatigue and optimizing cost. It enables SOC teams in mid‑size to large enterprises to close blind spots in minutes rather than months.
Funding
Funding not disclosed
Founders
Product
Problem
Security teams often miss critical threats because their detection rules lag behind rapid attacker innovation, creating blind spots, brittle detections, and high alert fatigue. Manual creation and maintenance of production‑grade detections across diverse stacks consumes engineering resources and cannot keep pace with changing environments.
Solution
Spectrum automates the entire detection lifecycle to keep security operations aligned with fast‑moving threats. It continuously maps coverage gaps by merging external threat intelligence with an organization’s internal findings, then automatically authors, tunes, and deploys production‑grade detections across SIEMs, data lakes, and other security tools. Ongoing monitoring identifies drift and breakage, automatically fixing issues to maintain detection health. The platform also optimizes alert volume and cost, reducing noise and freeing engineering time. By delivering machine‑speed detection updates, Spectrum enables teams to close blind spots in minutes rather than months.
Target Audience
Primary customers are security operations teams and SOC analysts in mid‑size to large enterprises that manage complex, multi‑layered security stacks and need to maintain up‑to‑date detection coverage.
Features
- Continuous coverage monitoring that combines external threat intel with internal findings to surface blind spots
- Automated detection authoring, tuning, and deployment across multiple security platforms (SIEMs, data lakes, etc.)
- Real‑time drift detection and self‑healing mechanisms to keep detections effective as environments change
- Alert‑fatigue reduction through noise filtering and cost optimization
- Unified dashboard that visualizes detection posture, coverage gaps, and remediation status