Our ML testing & governance product offering makes building, improving, launching, and maintaining reliable ML models simple and easy.
Reliable ML in 3 easy steps:
Run Model through Testing Suite
Improve Model by mitigating new risks
Monitor Reliability in Production
The testing suite is the core of the Wizard AI product. Once you've finished modelling, simply use our SDK to check your model's robustness.
We essentially PenTest your model, just as you would a new piece of software, to uncover your data+model vulnerabilities and risks that would be exploited in production.
Battle-tested fairness framework to verify how fair your models are on an individual and global level
Synthetic data PenTesting tools to simulate data draft, and stress-test your model to ensure they remain robust against expected market trends
Cutting-edge XAI techniques can crack open black box models and provide explanations to your modellers and stakeholders
Clear compliance checks to ensure your models satisfy company and governmental regulatory requirements
Once testing is complete, Wizard will collect all discovered risks and provide an easy to consume report with model explanations, compliance requirements, audit results, and vulnerabilities that should be addressed.
We also provide immediate solutions to this risks via re-training and data augmentation
Easily Consumable report to share with stakeholder and provide context to other modellers
Data Augmentation to improve performance across minority classes and data drift discrepencies
Reduce model debugging time (often a full sprint!) by over 95% while increasing model performance & efficiency
Discover 2.8x more severe bugs than traditional debugging
Finally, we constantly audit your models in production to ensure they adhere to Reliable AI principles, and act accordingly the moment they fail.
Remember: Reliable ML practices do not start until a model is in production!