Predictive Multi-variate Advanced Analytics

Overcome the limitations of PCA, PLS, and traditional univariate statistics with sophisticated ML when multivariate relationships are non-linear.

Make the shift from reactive to predictive monitoring

Use contextual process and analytical data from illuminator and Quartic AutoML to transform your multivariate analysis from reactive investigations to online predictive monitoring with a few clicks!

  • Increase time to value with online multi-variate analysis by 10x 
  • Move from hindsight investigations and DoEs to operational certainty
  • Shift key process attributes to an optimized state faster  
  • Move from traditional MPC (Model Predictive Control) to ML based unit optimizers

A better way to MVDA

The existing products and tools provide fragmented capability and focus on automating traditional statistical techniques that are limited to working on simple datasets. As a result, these techniques fall short when supporting richer, multi-dimensional data problems. Productionalizing these customized models is also time consuming, expensive, and inefficient

  • chip

    Glass-box AI

    Accelerates model development by engaging the subject matter expert and leveraging their knowledge

  • server-1

    Built for Big Data 

    Use larger, richer data sets, and new data sources to build more powerful models  

  • problem-solving

    Problem-solving workflows 

    Focus on problem solving rather than algorithm trials

We used PCA successfully to solve process problems, but the custom models for the complex, non-linear dynamics required a lot of coding and were hard to deploy. The Quartic MVDA solution provides us more power with easy deployment

— Large chemical industry user
The Quartic MVDA Solution is built on the Quartic Platform. The Platform connects to industrial OT (Operational Technology), condition measurement systems, MES, and CMMS systems; contextualizes the data to an asset and allows users to build intelligence agents using machine learning (ML) and complex event (rules) processing (CEP).