I like the automated alert investigation cross tool visibility and the clear reasoning behind simbians security decisions

I am a cyber security engineer at a mid-sized organisation and we have Simbian as our AI-powered security copilot in the Security Operations Centre (SOC). It integrates seamlessly with our current SIEM and EDR solutions, enabling my team to leverage natural language search capabilities to delve deeper into intricacies of alerts, automate recurring log evaluations, and rapidly develop incident response summaries without constantly switching between dashboards. The thing that I like the most is that it's a force multiplier for our comparatively small security team. A junior analyst has to spend many hours coding a great deal of complicated regular expressions, or learn a new query language for end users to query a particular log or a group of logs for a host that communicated with this malicious ip address during the past 48 hours, but with this new feature they can just type a question like show me all hosts that communicated with this malicious ip address over the last 48 hours. Simbian interprets that purpose, then traverses our interlocked equipment and provides an integrated overview. It has transformed our initial triage process and made it much faster. I also appreciate how fast it comes up with an easy to read summary of an incoming security alert with context—this can save us a lot of manual documentation time during the active investigation.

Working in a SOC means constantly drowning in thousands of daily alerts, the vast majority of which are false positives. What sets Simbian apart is its agentic AI approach to handling Tier 1 triage. Instead of relying on rigid, pre-built playbooks, the AI SOC agent autonomously investigates alerts the instant they arrive by collecting evidence across our entire stack pulling from our SIEM, EDR, and identity tools. It follows the evidence, evaluates observables, and categorizes each alert as a True or False Positive with a clear severity level and confidence rating. I love that it provides an auditable, replayable reasoning chain for every decision, so I can see exactly why it classified something as benign. The fact that it continuously learns from human feedback and writes its findings back into a shared Context Lake means it gets smarter and more accurate over time.