Powerful resources for intelligent data analysis
Setting industry standards with the most advanced machine learning and chemometrics software available.
Solutions for working with or without MATLAB on all platforms, including Windows, macOS/Mac OS X and Linux. Offering the widest available array of data preprocessing and analysis methods, with transparency and freedom to customize – all at the best price/performance ratio in the industry. Choose from our stand-alone or MATLAB-based packages:
- Multivariate calibration and pattern recognition with PLS_Toolbox and Solo
- Image analysis with MIA_Toolbox and Solo+MIA
- On-line predictions with Solo_Predictor and Model_Exporter
- Additional advanced and Custom Software Tools
Experienced Consultants for Every Discipline.
Our consulting staff has 100+ man-years experience applying chemometric techniques in a wide variety of applications, including:
- Chemical processes
- Semiconductor manufacturing
- Consumer products, food & beverages
- Analytical instrument development
- Medical devices
- Oil, chemical & plastics
- Metal & minerals
- PAT – Process Analytical Technology
- Hyperspectral imaging & remote sensing
- Electronic nose & sensor development
At EVRI we believe that the best data analysts are the people that own the data and understand the chemistry and physics behind it.
That’s why we’re always pleased to teach machine learning to analytical chemists and engineers involved in discovery through implementation.
Upcoming Events & Courses
May 7, 2023 - May 12, 2023
Eigenvector University 2023
Washington Athletic Club, Seattle Washington
Check out our training page for EVRI's full list of conference courses for the next year.
EigenU Online now also available! Due to popular demand we’ve made our three-day Basic Chemometrics Short Course available through EigenU_Online. Learn chemical data science in the comfort of your own home or office! EVRI can also deliver Customized Training to your site. Material can be drawn from our expansive course catalog or developed using your own data. This can be cost effective for as few as 3-5 participants.