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.
CMC Biotechnology Company
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.
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 how SVEM’s methodology sparks breakthroughs in various industrial applications?
Read the latest research.
Explore how SVEM’s methodology has been rigorously researched and validated to achieve flexible, robust, and reliable models for today’s complex operational processes in various industries.
SVEM for low-temperature fracture energy of asphalt mixtures
Journal article published in the International Journal of Pavement Engineering
SVEM for optimizing a glycosylation analytic method in biologics
Journal article published in BioProcessing Journal
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