ML Integrity, Delivered
Machine learning models fail.
Prevent bad outcomes with the only end-to-end solution.
Trusted by data science teams at
Models fail in the real world
AI is eating the world, but the ML models that power intelligent applications are prone to failure. Data science teams are always on alert, reacting to changes observed in dashboards and writing ad hoc tests. The need to constantly firefight model errors introduces risk and makes it difficult to apply ML at scale.
E2E Platform for ML Integrity
ML Integrity means that your models work as intended. It requires a rigorous approach to testing, monitoring, and improving your models. Robust Intelligence provides a platform that ensures ML Integrity throughout the model lifecycle
The Robust Intelligence Platform
AI Stress Testing
Before models are put into the wild, we proactively run hundreds of tests to automatically identify potential issues and suggest improvements for model production readiness.
Once models are ready for deployment, we automatically configure and deploy a wrapper around your model to prevent bad data from entering your system in real time.
increase in data science team productivity through automated testing and monitoring of ML models
more models deployed into production per year
decrease in the mean time to resolution of production machine learning issues
reduction in cost and time for model compliance verification