Watch Agentic SecOps in action at Black Hat
See Event Details
Anvilogic automatically investigates every alert, filters out recurring noise, and escalates the threats that matter with complete case summaries, timelines, and evidence already assembled. Analysts spend less time gathering context and more time responding.
Your analysts shouldn't spend their day deciding which alerts deserve attention. The Anvilogic Triage Agent evaluates every alert as it arrives, escalates the threats that matter, and recommends tuning for recurring noise before an analyst opens the queue. The result is fewer false positives, faster investigations, and a queue that's already prioritized.
Every SOC investigates differently. Blueprints turn your team's runbooks into AI-powered workflows that execute the way your analysts already do. Start with proven investigation Blueprints, or customize your own with a no-code visual builder.
When an investigation confirms a threat, Anvilogic can trigger response actions directly from the investigation. Isolate a host, disable an account, kill a process, or hand off to your existing response tools without leaving the platform. Because Anvilogic works with the security stack you already have, you can automate response while keeping your existing workflows intact.
Every investigation automatically becomes a complete case. AI captures evidence, drafts case notes, builds timelines, and records every analyst and AI action as the investigation unfolds, giving your team a complete audit trail without the manual work.
“
The impacts that AI makes across the detection lifecycle, from tuning, to reducing false positives in alert monitoring, to leveraging a cost-effective lakehouse, fundamentally transform the detection engineering process.
“
By using a detection engineering platform on top of our data lake, we are able to achieve some significant efficiencies in our overall SOC and IR operations, which can equate to cost savings of close to 70–80%.
“
Anvilogic is the perfect solution because it doesn't depend on any specific underlying data lake or SIEM solution. It isolates and abstracts the layer of data storage down to the schema, so we don't have to worry about making a big decision for the underlying storage solution. Instead, we have the flexibility to plan for the future.
