Predictive models you can actually interpret.

Interpretable machine-learning models that find the combinatorial biomarkers driving disease, response and outcome — with every predictor traceable to the evidence behind it, so you don’t trade accuracy for a black box.

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Overview

Stop choosing between accuracy and interpretability.

Most multi-omics signal comes from combinations of features. Predictive Modeling lets you build models that surface those combinations: which transcripts, mutations, cell types, and clinical variables together predict the outcome.

Every trained model is interactively explorable — feature contributions, SHAP-style importances, and the underlying KG evidence that supports each predictor.

Stop choosing between accuracy and interpretability.

Predictive Modeling outputs become inputs to Clinical Trial Analysis and Target Discovery — biomarkers don't live in a silo.

Predictive Modeling App App Engine SHAP-style explanations

Get in touch

See Predictive Modeling in action.

Walk through this solution with an applications scientist — focused on the questions that matter to you.

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Predictive models you can actually interpret.

Stop choosing between accuracy and interpretability.

Stop choosing between accuracy and interpretability.

Solutions that pair well with Predictive Modeling.

See Predictive Modeling in action.