We are pleased to share that the first part of a two-part post on AI for Enterprises in their website. Part 1 focused on data quality effects titled - "AI for Enterprises. Part 1: Where Are We in Tackling the Popular Adage GIGO?" is published by the Massachusetts Technology Leadership Council (MassTLC). The post by our CEO, Suresh Gopalan, centered on the current status in tackling data quality, effects on outcomes and consequently on designing robust and effective digital and AI transformation strategies. The post outlined ReSurfX solutions where we leverage our novel machine learning approach 'Adaptive Hypersurface Technology' (AHT) in our emerging solutions as well as the ones already in the enterprise SaaS product ReSurfX::vysen. The post highlighted causes for current problems, implications, current efforts and ReSurfX solution based on the premise that our CEO Suresh Gopalan had highlighted in the showcase interview published CIO Review in 2017 together with ReSurfX being recognized as 20 Most Promising Data Analytics Solution Providers in 2017. The premise we posited while building AHT and solutions for our customers currently though the SaaS product ReSurfX::vysen is that: “dramatic improvements in accuracy and novel insights can only happen through innovation outside the mainstream framework – given that error properties are often non-uniform in big data, and most analytic shortcomings result from model assumptions not robust enough to handle that”. That approach has proven very effective in every solution we develop and tested in scale have proven to be the "best-in-class". Suresh Gopalan expressed not only expressed his thanks to our team who continue to explore, innovate, build and execute these powerful solutions, as well as our MassTLC and their team for spotlighting that post in their newsletter of June 22, 2022. A section with the copy from that spotlight in MassTLC newsletter is here.

A longer version of above-mentioned post with same title, but with more details is posted on our website which covers the solutions in ReSurfX::vysen product, unprecedented outcomes and proof of every value proposition of ReSurfX from the beachhead applications using gene expression, broader applicability based on the data properties, and additional rationale for that choice.