In this episode of Reinventing Retail, we find out how predictive analytics are giving retailers the power to make data-driven decisions that will forever change assortment planning. Our guest is Richard Wright, VP of merchandising for Predictix: a leading provider of retail machine learning solutions. Infor announced it had completed its acquisition of Predictix on June 28, 2016. Using the artificial intelligence of machine learning technology, retailers are able to forecast potential market fluctuations and trends--with the agility to quickly adapt when disruptions are imminent. Hear what Richard has to say about this next generation retail tech, and subscribe to Reinventing Retail on iTunes for more episodes.

Infor, a leading provider of business applications, has announced the acquisition of Predictix, a provider of machine-learning solutions for retailers. Predictix will become part of Infor CloudSuite Retail, a new suite of enterprise applications delivered in the cloud and designed for today's retailing landscape. The acquisition comes six months after Infor announced an investment in Predictix. "The synergies between Infor and Predictix were greater than we could have hoped, and we've come to appreciate a great cultural alignment where both teams have passionate people who work hard and want to make a difference in retail and beyond," said Charles Phillips, CEO of Infor. "Buying out the other Predictix investors makes sense to bring the teams together and provide the scale and resources needed to accelerate the retail revolution."

Do you remember what it was like the first time you got your hands on an iPhone? When you realized that all the things that you used to have to do on separate devices now could be accomplished on one single device? Well, the minds behind LogicBlox would like you to feel the same way about its foundational technology that collapses multiple technology stacks into a unified smart database environment that aims to enable enterprises to create sophisticated and easily iterated applications in one place. Transaction and analytics co-exist in the platform, with the system utilizing a single declarative language with extensions – such as Machine Learning capabilities and statistical relational models – to support prescriptive and predictive analytics. Users can leverage LogicBlox' full-blown database functionality to train Machine Learning models, for use in solving forecasting or optimization problems, for instance.