PLS_Toolbox 5.2 and our stand-alone product Solo 5.2 were released on April 7. We've added some new functionality plus a host of improvements "under the hood" that make PLS_Toolbox/Solo more efficient and flexible.
Our main model-building interface, Analysis (shown at left), has been updated to allow much more flexible data loading and management. You can now view how your model applies to test data instantaneously. New visualization tools make it easier to find trends in your data and quickly identify what those trends mean. Plus the "linking" between data, variables and samples has been improved to help you sort through your data.
Many of our standard features have been enhanced including an improved Model Cache with additional data management features and new Model Robustness Testing tools (shown below right) which allow you to determine how your model will hold up over time. 
Other new features in version 5.0 included the addition of new data importing options (including improved text-file importing and support for Hamilton Sundstrand ASF, AIF, and BKH files), new preprocessing methods and visualization, new clustering method, dbscan, and an automatic creation of model building scripts to reproduce any model.
Not familiar with Solo? Our stand-alone product, Solo, lets you use the main analysis tools from PLS_Toolbox in a purely point-and-click environment. Solo is powered by MATLAB® libraries, so you get MATLAB's numerical accuracy and speed. But you don't have to own MATLAB to use it. That's why we call it Solo! And all the new point-and-click features we add to PLS_Toolbox go directly into Solo as well.
Solo lets you do PCA, Multi-way PCA, CLS, PLS regression, PLS discriminant analysis, and even curve resolution and PARAFAC in the same intuitive interface. Like PLS_Toolbox, Solo allows users to edit data sets either graphically or in a familiar spreadsheet-like interface. Data can be imported from a variety of sources, including spreadsheets, MATLAB .mat files, Galactic .spc files, and delimited ASCII files. Solo uses the same DataSet Object format as Eigenvector's other MATLAB toolboxes