Solutions for Model Management

All models are wrong. Some models are useful if you know Why they are wrong. Model quality is evaluated globally but fit varies locally - bias and variance are rarely uniformly distributed, resulting in inconsistent model performance within the data topology. Data-driven organizations are looking for ways to augment their model development & management processes and MondoBrain elevates their ability to identify and understand model deficiencies in order to improve model performance.

Applications include:

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Identify and Diagnose

Data leaders need constant access to model performance management and diagnostic reporting in order to continuously improve their models. MondoBrain provides decision-makers with the ability to understand how model performance can be optimized in different data domains, as well as which models are better suited in those specific domains.

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Explain Model Behavior

The adoption of AI and machine learning in analytics has introduced a new layer of complexity to decision making. MondoBrain provides the ability to understand the "why" behind the uncertainty: why models are not working when they don't and why models are working when they do. MondoBrain can also explain in which combinations of dimensions and domains model accuracy is most sensitive to change.

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Improve Model Performance

MondoBrain connects the dots between the "why" and the "how", providing decision makers with better information on the contextual uncertainty of model predictions and how key insights can be used to help data scientists improve the original model.

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Reiterate and Continuously Improve

Rinse and repeat. Model management is a cyclical process. MondoBrain provides the necessary tools to continuously improve model performance, giving the end user the agility to adapt and adjust to evolving markets.

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