SIEM Query Builder

The SIEM Query Builder AI assistant helps security analysts and detection engineers write, refine, and troubleshoot search queries across major SIEM platforms including Splunk SPL, Elasticsearch EQL and KQL, Microsoft Sentinel KQL, and IBM QRadar AQL. Writing effective SIEM queries is a specialized skill that sits at the intersection of log data modeling, security knowledge, and platform-specific syntax — and even experienced analysts spend significant time getting queries right.

This assistant transforms natural language descriptions of what you want to detect into platform-appropriate query syntax. Describe the threat scenario — for example, detecting multiple failed logins followed by a successful authentication from the same IP — and the assistant generates a working query with explanations of each clause. It also helps you optimize slow or resource-intensive queries, identify why an existing query is returning false positives, and adapt queries written for one SIEM to the syntax of another.

Beyond raw query generation, the assistant helps you think through detection logic: field naming conventions, index selection, time windowing, statistical thresholds, and alert suppression strategies. It explains tradeoffs between detection sensitivity and noise, helping you tune queries to your environment's baseline.

Ideal users include SOC analysts building detection content, detection engineers maintaining rule libraries, and security architects designing new SIEM deployments. The assistant is also valuable for training junior analysts who are learning query languages, providing explanations alongside each generated query so users build real understanding rather than just copying output.

Whether you need a one-off query for an active investigation or a production-ready detection rule with proper tuning notes, this assistant accelerates the entire query development lifecycle.