Each of Andeavour's products is detecting, illuminating and preventing dangerous unseen trends across your organization before they become critical security incidents.
Identify new attack patterns and threat vectors before they become widespread security incidents
Example: Early detection of zero-day exploits and advanced persistent threats
Analyze historical data to predict potential security vulnerabilities and system weaknesses
Example: Predicting ransomware targets based on infrastructure patterns
Uncover non-obvious relationships between security events across different systems and timeframes
Example: Linking seemingly unrelated log entries to sophisticated attack campaigns
Collect security data from multiple sources and timeframes
Apply AI algorithms to identify subtle patterns and anomalies
Connect seemingly unrelated events to reveal dangerous trends
Provide actionable insights to prevent security incidents
Detecting long-term, stealthy attacks by correlating subtle indicators across months of data.
Identifying unusual access patterns that may indicate malicious insider activity.
Early detection of compromised third-party components and dependencies.
Organizations using our trend detection capabilities report significantly improved security posture with proactive threat prevention rather than reactive incident response.
Inside the Agentic SOC, trend detection runs as a continuous background process rather than a scheduled batch job. Every new event is scored against active candidate trends in near real time, so a trend's risk score updates as soon as a corroborating signal arrives, instead of waiting for the next analysis cycle.
Scoring combines statistical baselining for volume and frequency signals with sequence-aware models for order-dependent behavior, such as a specific sequence of authentication and data-access events that resembles a known attack chain from MITRE ATT&CK.
Trend scores and their supporting evidence feed directly into the same case management workflow used by AgentGuard for agent-level enforcement, so an analyst investigating a rising trend can pivot directly to the specific agent or account actions that produced it without switching tools.
Full detail on how scores are validated against historical incident data is published in our methodology.
No. It is designed to reduce alert volume by grouping related low-severity events into a single scored trend, rather than adding a new independent alert stream on top of existing tools.
Yes. Trend detection consumes the telemetry you already generate and complements existing rule-based and signature detections rather than replacing them.
See our what is an Agentic SOC page and our published research for supporting data.
Organizations that adopt trend-aware detection inside the Agentic SOC typically report earlier intervention points on multi-stage attacks, meaningfully fewer isolated false-positive alerts reaching an analyst's queue, and less time spent manually stitching together events from separate tools to understand whether a pattern is actually escalating.
Because trend scores update continuously rather than on a fixed schedule, security teams gain a live picture of which risks are accelerating right now versus which have stabilized, which materially changes how limited analyst attention gets allocated during a busy shift. Outcome measurement methodology, including how baseline behavior is established and validated, is published on our methodology page.
Don't wait for security incidents to happen. Illuminate dangerous trends before they impact your organization with our advanced AI-powered detection capabilities.