Query.AI Federated Detections vs Rilevera: Side-by-Side Comparison (2026)

Query.AI Federated Detections: Runs security detections across distributed data sources without SIEM ingestion. built by Query.AI. Core capabilities include Federated detection execution across distributed data sources without ETL or data centralization, Detections authored in Federated Search Query Language (FSQL) with windowed aggregations, grouping, and threshold logic, Deterministic, scheduled detection execution with recorded evaluation windows and audit metadata..

Rilevera: AI platform for continuous detection rule validation, optimization & governance. built by Rilevera. Core capabilities include Continuous detection rule validation across platforms, AI-driven detection optimization and false positive reduction, MITRE ATT&CK coverage and gap analysis..

Both serve the Detection Engineering market but differ in approach, feature depth, and target audience.

Query.AI Federated Detections differentiates with Federated detection execution across distributed data sources without ETL or data centralization, Detections authored in Federated Search Query Language (FSQL) with windowed aggregations, grouping, and threshold logic, Deterministic, scheduled detection execution with recorded evaluation windows and audit metadata. Rilevera differentiates with Continuous detection rule validation across platforms, AI-driven detection optimization and false positive reduction, MITRE ATT&CK coverage and gap analysis.

Query.AI Federated Detections is developed by Query.AI. Rilevera is developed by Rilevera. Vendor maturity, funding stage, and team size can be important factors when evaluating long-term viability and support quality.

Query.AI Federated Detections integrates with SIEM, Cloud services, SaaS platforms, Object storage, Data lakes. Rilevera integrates with SumoLogic, AWS CloudTrail, Cylance. Check integration compatibility with your existing security stack before deciding.

Query.AI Federated Detections and Rilevera serve similar Detection Engineering use cases: both are Detection Engineering tools, both cover Detection Rules. Review the feature comparison above to determine which fits your requirements.