Accelerate time-to-market by bridging the gap between machine learning and design of experiments

Develop better products. Improve existing processes. Extract more experimental insights. Build more accurate predictive models. And do it all in less time and at a lower cost with Self-Validated Ensemble Modeling (SVEM).

Self-Validating Ensemble Modeling platform: builds accurate and validated predictive models in 25% of the cost and time of using conventional techniques

SVEM enables you to build predictive models with a very high degree of accuracy quickly and cost-effectively by combining the power of machine learning and DOE.

Improve prediction accuracy

While traditional designs of experiments tend to generate 30 or fewer observations, machine learning generally needs thousands of observations to be effective. SVEM combines the best of both of these methods, allowing you to look at more variables per run, conduct fewer trials, and build more accurate predictive models from small data sets.

Overcome limitations in experimentation

With SVEM, you can examine a higher number of experimental variables, allowing you to see the entirety of a system. As a result, you get higher order, predictive models that are more realistic, detailed, and reliable—ultimately leading to more successful experimental outcomes in fewer runs.

Extract more information with fewer resources

The power of SVEM’s bootstrapping algorithm enables you to explore more product and process predictors than using conventional DOE. This means you can generate more comprehensive information with fewer experimental trials.

I really appreciate your teams efforts with regard to the modelling. It’s a bit of a shock to see an imperfect set of data like we provided get turned into a model that can predict process outputs with that degree of confidence.

Vice President
CMC Biotechnology Company

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Research and development unhindered by conventional methods

Engineers and scientists need to learn faster, but they are limited significantly by conventional methods. By leveraging machine learning, SVEM enables you to make more informed predictions and bring high-quality products to market in record time.

Stability reinforcement in model-building algorithms

Extremely flexible model building

Validation for small data sets

The pace of change in today’s world is unprecedented. Engineers, scientists and other knowledge workers need SVEM to reduce the uncertainty around scientific inquiry and build trustworthy products and processes despite fierce competition in the marketplace.

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Getting started

Do you have questions or need more information about SVEM?

Get in touch to explore how SVEM can benefit you and your engineering and science teams.

Want to learn more about SVEM’s methodology?
Watch our webinar.

Learn about how SVEM’s methodology has been rigorously researched and tested to achieve reliable results in real-world, industrial scenarios.

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