It also happens to be the format of much of the most valuable data in modern organizations. Robust Intelligence ensures the integrity of your tabular ML data models, enabling you to confidently build on top of real world data.
Check your data for outliers, drift, and broken data pipelines. Check your model for equal performance across subsets of the data, sensitivity to small perturbations, performance on outliers, data pipeline error handling, and robustness to adversarial attacks.
Automatically protect your model in production from aberrant data points with an auto-configured Firewall that tests each incoming data point in real time. Take action against bad inputs so they never reach your model.
Continuously monitor the behavior of models in production to identify issues, understand when it’s time to retrain a model, and automate root cause analysis of model failure. Enable rapid remediation to minimize model downtime.
We offer native support for many different model tasks, such as binary classification, multi-class classification, regression, and ranking.
Test any type of model (statistical, tree-based, neural net, etc.) and pull data from any source (local, networked, cloud) using our simple and flexible abstractions.
Robust Intelligence scales to the data sizes of the modern enterprise, allowing you to efficiently test across billions of rows with thousands of features.
The Robust Intelligence testing framework incorporates hundreds of tests. Let your data science teams focus on building innovative models, confident in the knowledge that our engineers continually add tests from the bleeding edge of ML research.