Independently validate any AI model or data and generate quantitative AI risk metrics at scale.
Our approach is not to replace your existing AI investments. Instead, our AIMI platform sits as a layer on top of current AI assets or embedded within your existing workflow.
Taxonomy based edge case testing & statistical noise injection for jitter analysis.
Statistical metrics generated from the data showing the risk of reidentification, paired with Membership Inference Attack privacy risks on the model.
Genetic algorithm synthesis function for adversarial attack profiling, with distance based algorithm for sorting & filtering.
Synthetic discovery algorithm paired with iterative model training, for AI model IP protection & informed security posture.
Multi-step bias identification against configurable sensitive attributes with statistical disparity testing and hidden relationship profiling
Threshold indexed performance metrics, for fairness of quality of service comparison.
Pair-wise distance based method that determines similarity between test and train data. Language and semantics are captured in text.
Perturbation for tabular data, ablation with language profiling for text, and search, heuristics & topologies for image data.
The Executive Dashboard is for strategic decision makers who decide what does or does not go into production. It enables a portfolio view of AI model risks which in turn require human oversight.
Fail
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