ReSurfX
Premium Data Accuracy for Better Outcomes

The true value of big data lies in harvesting it for making informed decisions that improve business outcomes. However, with the proliferation of data, companies across industries are struggling to find new ways of utilizing data and are seeking superior value-based business models and highly sensitive measurement technologies to reduce analytic errors. Based in Cambridge, MA, ReSurfX is developing a new breed of ‘Big Data’ technology that deals with both data generation and utilization for effective decision making. ReSufX posits 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. “Adaptive Hypersurface Technology (AHT) of ReSurfX is one such novel framework that facilitates superior outcomes and ROI through significant robustness to unknown error properties to improve accuracy, uncovering new insights that also brings an inherent degree of personalization.”

“Our approach is to provide a novel data analytics platform as well as target premium measurement technologies for reducing analytical errors at each stage of the workflow, thus making a large improvement in sensitivity, accuracy, and effective use of data,” says Dr. Suresh Gopalan, CEO and Founder, ReSurfX.

ReSurfX is geared to provide innovative classes of solutions for the effective use of large volumes of data through strategic design of measurement technology, implemented as hardware/component level changes, as well as a data analytics solution which focuses on sensitivity and accuracy. These solutions enable analytics on each data source and in successive combination of data sources, enabling newer value based business models, and highly sensitive measurement technology outputs.

ReSurfX’s vysen—is an enterprise grade SaaS analytics platform for the life sciences and healthcare sectors. “vysen is powered by our patented, and proprietary Adaptive Hypersurface Technology to make better decisions on outcomes through superior accuracy and novel insights, improving innovation and ROI” states Dr. Gopalan. vysen integrates with numerous stages of the workflow and complements preferred solutions and infrastructure built around specific data and applications in an enterprise.

vysen is powered by our patented and proprietary Adaptive Hypersurface Technology to make better decisions on outcomes through superior accuracy and novel insights, improving innovation and ROI

ReSurfX’s core AHT is a datasource agnostic and targets a pervasive data property to adaptively identify many combinations of inputs that can lead to an outcome of interest.

Major applications of ReSurfX’s portfolio include healthcare, finance, targeted marketing, and manufacturing. “But our focus is specifically on healthcare where clients are facing tremendous challenges in drug discovery and development pipelines, and health care utilization efficiency,” points out Gopalan. ReSurfX’s solutions to evidence-based medicine, point-of-care products, and personalized medicine make medical care more accurate and efficient, thereby adding tremendous value to the life science and healthcare sectors.

ReSurfX has served organizations in the healthcare sector to reduce false positives as well as to identify overlooked “hits” through analytics—facilitating effective use of manpower and other resources. In one instance, ReSurfX enabled a research unit developing personalized and evidence-based medicine to make novel discoveries and prevented the publication of faulty analytics.

Recently, ReSurfX launched its redesigned version of vysen as a scalable platform for repository-scale processing to deliver large increase in enterprise efficiency that initially deals with microarray and RNASeq based gene expression data. “We will continue to empower customers and build additional applications and features into our platform to solve a variety of problems end-to-end,” concludes Gopalan.