Kenzo Agentic Detection Platform is a security operations tool that uses agentic AI to enhance detection engineering capabilities. The platform analyzes unified security data to automatically generate new detection rules, tune existing rules, and chain notable events together. The platform continuously monitors security rule coverage against the MITRE ATT&CK Framework and threat intelligence reporting to identify gaps and recommend new detection rules. It provides autonomous rule generation capabilities to address coverage gaps in security environments. Kenzo dynamically tunes noisy detection rules that generate large volumes of alerts based on alert performance, feedback loops, and environmental context. This tuning approach aims to maintain maximum coverage while avoiding over-tuning that could lead to false negatives. The platform includes context-aware detection chaining functionality that links isolated events across users, systems, and time to surface multi-step attack patterns. This enables behavioral analysis and detection of threats that may evade traditional alert logic. Kenzo is designed to augment existing SIEM and security stack infrastructure by adding AI-native security operations capabilities to legacy systems.