twinLab™, digiLab's world-leading machine learning product, combines the latest methods in uncertainty quantification (UQ) to build real-time emulators for complex engineering challenges.

Product Overview

Acquire > Train > Predict

While convential methods require vast amounts of data, twinLab can produce a surrogate model of real-world scenarios for you to make predictions and inform your decision making with only a limited set of data.

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Are you interested in understanding how twinLab works?

Why twinLab?

ML You Can Trust

Once you have used twinLab to create your surrogate model, its unique ability to quantify uncertainty in its predictions gives you the confidence you need to start relying on it when it matters, in a safety-critical setting.

Supercharged Design Cycles

It can be time-consuming and expensive to understand what data is needed to create the optimal surrogate model. twinLab’s active learning can recommend the next points to collect data for. This reduces design cycles and leads to a viable surrogate model, faster.

Augment with Expert Knowledge

Apply expert knowledge of your data to adjust your surrogate model or leave twinLab to make intelligent decisions in the generation of your surrogate model. Either way, twinLab works for you.





Our no-code Excel plugin is designed so that twinLab fits perfectly with your workflow.


The twinLab Python client library gives you the power to make twinLab work in the way that you want.


Automate your workflow and get realtime predictions by plugging twinLab into a wider system.

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