Citrusx

Founded 2021

Validate, monitor, and explain machine learning and language models to reduce risk

You can use Citrusx to validate, monitor, and explain machine learning and large language models across development and production. The system alerts your team when a model makes mistakes or drifts in accuracy. You can detect bias, pinpoint vulnerabilities, and generate detailed compliance reports aligned with AI regulations like the EU AI Act. Teams can compare models, evaluate individual predictions, inspect data clusters, and provide clear explanations to auditors, data scientists, and executives to keep systems safe, fair, and reliable.

What Citrusx does

Validate model stability before deploymentInspect feature importance for specific predictionsSet up alerts for performance drift and anomaliesExport audit-ready governance documentationScan models for bias against protected groupsTest model resilience against manipulated inputsEvaluate model accuracy across different user segmentsTrack model performance and detect drift in real timeExplain individual predictions and group-level model decisionsDetect bias and identify vulnerable data segmentsGenerate automated compliance reports for regulations like the EU AI ActReceive immediate alerts when deployed models make errorsCompare different models to check benchmarks and KPIsIdentify data features that disproportionately sway model output