Build robust, reliable
AI systems
Apply leading-edge ML validation and robustification for exceptional resilience
Learn moreOur approach
-
Validate
Access deeper analysis of model performance & robustness. Identify fragilities and counter examples. Formally verify regions against broad classes of perturbations. Analyze deep neural networks, decision trees, and random forests.
-
Robustify
Analyze whole regions of input space – not just points – and check performance under domain shift. Remove fragilities, improve fairness and lower variance by reducing unexpected behavior in trained models.
-
Monitor
Automate, build, and verify with continuous monitoring alerts. Track standard model metrics over time, plus gain the ability to watch for any new fragilities or emerging issues.
1/3
