AlistoIR uses AI to support SOC triage with summarization, context shaping, and investigation guidance so analysts can move faster through noisy queues without handing over final response decisions.
This workflow is useful for teams dealing with repetitive alert review, inconsistent triage quality, or long queues that slow down investigation and escalation.
AlistoIR uses AI as an analyst support layer, not a replacement. The goal is to help the team reach a clearer starting point faster, with enough context to decide what should happen next.
Each capability below exists to help security teams move from alert context to accountable response without stitching together disconnected tools.
Turn dense alert data into faster first-pass triage context so analysts can see what deserves attention sooner.
Use AI to support investigation direction while keeping escalation, case decisions, and actions in analyst hands.
Keep AI triage connected to cases, artifacts, and broader response workflow instead of isolating it as a standalone chatbot feature.
Teams usually get the most value when the workflow and operating model below already match how they handle incidents today.
Common questions about how AlistoIR supports this workflow.
No. The intent is to support analyst speed and clarity, not to replace human judgment for important triage and response decisions.
SOC teams with noisy queues, limited analyst time, or a need for more consistent first-pass triage across shifts.
In AlistoIR, the AI output is tied to actual security workflow such as alert review, case handling, observables, and investigation context.
Yes. It can give less experienced analysts a stronger starting point while still letting senior reviewers control final direction and escalation.
Tell us about your Wazuh deployment, response process, or client operations model and we can show you where AlistoIR fits without requiring a full rip-and-replace of your existing stack.
