The Robust Intelligence platform

Proactively eliminate AI failure at every stage of the ML lifecycle.

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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 Stress Testing

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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 Firewall

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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
Line graph about abnormality rate over time
AI Continuous Testing

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Stress Testing, Firewall, and Continuous Testing work together to achieve ML Integrity

At the core of the test-based approach of the RI Platform 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 to the specific forms of failure to which a given model is susceptible. Finally, Continuous Testing runs these tests during production, and the test based approach offers automated root causing since the failure of a single test reveals the underlying cause of that failure. Using all three elements of the RI 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.

Any data

Any model

Any platform

"Robust Intelligence helps our data science teams standardize our pre and post-production ML testing practices, reducing time-to-production and the inherent risk associated with ML deployments. Expedia runs hundreds of models in production, developed by multiple teams, which serve hundreds of millions of predictions a day. Robust Intelligence enables our data science teams to continue building cutting edge AI models while minimizing failures."
Dan Friedman
VP of Data Science
"As the FDA continues to emphasize removing bias in ML models, the Robust Intelligence Platform is well-positioned to ensure that models in production are robust in a standardized, automated fashion while also being flexible enough to comply with rapidly evolving regulatory guidelines."
Alex Zhong
Senior Manager, Machine Learning & AI Research
"Using the Robust Intelligence Platform, we were assisted in the quality control process (which previously was carried out manually) and proceeded with development more efficiently, robustly, and uniformly. The technical skills of the Robust Intelligence engineers are extraordinary."
Eiji Yoshida
Head of IOWN Innovation Office
“Robust Intelligence serves as a guidepost for us to instill machine learning integrity.”
Ram Bala
Sr. Principal Data Scientist
“Tokio Marine Group utilizes AI across various business areas, from claims services, product recommendations to customer support. Despite the immense benefits of AI, the more we apply AI into our business, the severer the consequences of AI risks are. Robust Intelligence provides unique and unparalleled offerings to identify and address AI vulnerabilities that are otherwise very hard to recognize. We are committed to working with them and further accelerating our business collaboration.”
Masashi Namatame
Chief Digital Officer
"Seven Bank leverages AI at the core of our ATM services and financial services, addressing societal needs and challenges from our customers’ perspective. Robust intelligence ensures the quality of such models, which are critical to AI utilization. By constantly guaranteeing the state of AI against changes in customer behavior, service needs, and other potential changes, RI enables us to take a big leap forward in applying AI to bring our services even closer to our customers."
Yoshiyuki Nakamura
Assistant General Manager, Corporate Transformation
"As companies operationalize AI at an accelerated rate, the consequences of model failure are amplified. Companies must put in measures throughout the model lifecycle to eliminate negative social and economic impact. Robust Intelligence, which instills integrity in ML models, brings additional strength to NEC’s extensive experience and knowledge in using AI. The companies will work together to build and operate AI systems in a safe, reliable, and fair manner for NEC's customers across industries."
Hitoshi Imaoka
Senior Director