The Robust Intelligence platform
Proactively eliminate AI failure at every stage of the ML lifecycle.
Overview
The Robust Intelligence Platform integrates seamlessly into your ML lifecycle to eliminate model failures. The platform detects your model’s vulnerabilities, prevents aberrant data from entering your AI system, and detects statistical data issues like drift.


AI Stress Testing
Discover and remediate model weaknesses before deployment
Value Props
Reduce risk of model failure with automated, comprehensive pre-deployment testing
Achieve model production readiness in minutes, not months
Use the powerful stress testing framework to create and share custom tests that meet your exact needs
Simplify model governance and compliance with autogenerated reports and intelligent insights
AI Firewall
Prevent model failures in production
Value Props
Eliminate silent model failures with real-time protection against anomalous data
Boost model performance in production
Add custom logic to automatically flag, block, or impute erroneous data in real-time
Dramatically reduce firefighting after model deployment
AI Continuous Testing
Monitor your model in production
Value Props
Detect anomalies and drift in your production data
Reduce model downtime with intelligent monitoring and root cause analysis
Gain visibility into production model behavior and know when it’s time to retrain your model
Track custom business metrics over time
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Stress Testing, Firewall, and Continuous Testing work together to achieve ML Integrity
At the core of our test-based approach is a single test. Each test measures your model’s robustness to a specific type of production model failure. Stress Testing runs hundreds of these tests to measure model production readiness. The results of these tests are used to auto-configure a custom AI Firewall that protects the model against the specific forms of failure to which a given model is susceptible. Finally, Continuous Testing runs these tests during production, providing automated root cause analysis informed by the underlying cause of any single test failure. Using all three elements of the Robust Intelligence platform together helps ensure ML Integrity.

AI Stress Testing
Detect Vulnerabilities

AI Firewall
Prevent Failures

AI Continuous Testing
Monitor Models
Robust Intelligence is Enterprise Ready
Flexible
Robust Intelligence is model architecture-agnostic and includes built-in support for tabular, NLP, and computer vision models, and treats your model as a blackbox so that you can use any model architecture.
Customizable
Configure the parameters of all default stress tests, and add custom tests and metrics that are important to your business.
Easy to use
Use powerful REST APIs and the Python SDK to programmatically access Robust Intelligence, allowing you to integrate into existing platforms and automate ML workflows. Use our intuitive UI to visualize and share results.
Scalable
Robust Intelligence seamlessly scales to process production workloads on the order of billions of data points and hundreds of models.
Robust Intelligence in your ML workflow
The RI Platform offers native integrations into your Machine Learning development pipeline. Connect seamlessly with your data, with your model, via your platform. An example workflow of how our platform helps maintain ML Integrity in your workflow.
Stream data and extract features from your cloud data storage.
Train your ML model.
Run Stress Tests on your model to evaluate its vulnerabilities and log the results to your experiment tracking framework.
Wrap AI Firewall around your model with one line of code and deploy to production.
Monitor model performance, and automatically diagnose and remediate issues with Continuous Testing.