Solve hard problems to achieve ML Integrity

Robust Intelligence can be applied to a variety of use cases across the machine learning lifecycle.
Enable teams to address a variety of use cases.
Deploying machine learning responsibly means validating models during development, monitoring models once they are in production, and checking that incoming data adhere to expectations before using the model. Robust Intelligence provides solutions for these different use cases, and more.

Model production readiness

Production-ready models need to be rigorously tested to ensure they are not overly sensitive, that they perform well across subsets of data, and that they effectively handle distribution shifts and abnormal inputs. Automatically test these principles in your CI/CD workflow with AI Stress Testing and ensure that models conform to your standard definition of production readiness.

Real-time model protection

Machine learning models are notorious for making confident but incorrect predictions on data points with outliers, missing values, unseen categories, and other abnormalities. Protect your model from unexpected inputs by using our AI Firewall to flag, block, and impute individual inputs that your model isn’t well-equipped to handle.

Model compliance assessment

Asserting that models are compliant with regulations before releasing them to the world is an important, but time-consuming, effort. It’s made effortless with Robust Intelligence. Select from our database of compliance-focused tests, synthesize the results into a report, and maintain an audit log of your production models.

Model monitoring

With data streams constantly shifting and evolving, a model trained last week might not be performing well today. Once your model is in production, use our AI Continuous Testing to monitor and alert on distribution drifts and abnormal inputs which may be causing your model to fail. Know when it’s time to retrain your model and automate the root cause analysis of model failures.

Model security (adversarial attacks)

Many machine learning models can be fooled by malicious actors into making incorrect predictions with virtually unnoticeable changes to the input, known as adversarial attacks. Harden your model against such vulnerabilities by using our suite of black-box adversarial attack tests to augment your data, inform your training algorithms, and identify your most robust candidate models.
"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

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