Xpanse AI reduces time-to-delivery of Predictive Models from months to minutes, allowing organisations to complete Predictive Analytics projects in few days.
Maciek Wasiak, CEO of Xpanse Analytics says: ”Over the last 10 years we have built hundreds of Predictive Models for companies and clients around Europe using Machine Learning and burning thousands of Data Scientist man-days. After so many projects we started to see some common pain points that kept cropping up in these types of projects.’
‘We started toying with the idea of sort of turning the Machine Learning techniques on themselves, coming up with ideas for algorithms that could automatically learn to prepare the data and build these models with minimal manual interventions. After a few months we developed a prototype and pointed it at a problem we had recently finished working on, only to see it spit out a finished model in a few hours – a project that we had just spent 6 months working on with a team of 4 data scientists and data engineers. After seeing the early promise, we wanted to develop this out to a tool that would make Predictive Analytics delivery blazingly fast.’
Predictive modelling has many applications and it is often used by companies to predict what their customers are going to do in the future – if a customer is going to leave to a competitor, if they are going to buy a particular product or if they are going to make a claim on an insurance policy.
‘Any Data Scientist who has built a predictive model knows the painstaking process of Feature Engineering – looking all at the data available and trying to ask the right questions to understand why a customer does something. This normally starts with workshops and brainstorming sessions with business experts to capture anecdotal knowledge and experience, then writing hundreds or thousands of lines of code to manipulate the data to test whether these anecdotes hold true.‘
‘Xpanse AI flips this on its head. Instead of limited guesswork, Xpanse AI automatically searches all the available information to find the patterns and behaviours that are actually relevant to your problem. It then explains the patterns in plain English, presents the insights visually and outputs the code to identify which customers to target going forward. Of-course you can add in your own expert knowledge into the process as well, but that isn’t required on the data preparation side of things.‘
Shane Teehan, a Director in Xpanse Analytics says ‘Xpanse AI can handle datasets of any scale and complexity through its cloud-powered back-end. And to ensure the greatest speed and ease-of-use, the user has access to an intuitive, point-and-click interface throughout the process – no coding needed. This is a platform that finally opens up the full power of Predictive Modelling to coders and non-coders alike. It provides organisations with a speed-to-deploy advantage of Predictive Models that will give you a real edge in your marketplace.’