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GryusBanking AI Robot

Interpretable AutoML at scale created by and for data scientists

Cloud and big data

Train data parallelization and leave subsampling behind.

Interpretable ML

Complete transparency regarding executed algorithms, resulting models and feature analytics for interpretability.

Monitored AI

Self-monitoring audit engine to ensure that every execution is aligned with the behavior expected.

The best predictive models, automatically trained

Cloud-based AutoML tool to continuously train predictive models by exploiting the freshest data available, reducing algorithmic-expert supervision and deploying to production effectively.

Key features

Algorithmic diversity

Harnessing extensive open-source ML algorithms, ranging from simpler methods, including logistic regression, to more complex ones, such as XGBoost, CatBoost and LightGBM.

Reporting & interpretability

Providing feature-importance rankings, partial dependence plots and human-interpretable explanations obtained from linear surrogate models.

ML-oriented monitoring

Monitoring tool that controls changes in acceptance rates, score distributions, model decisions and variations in data that define the target population.