The opportunity to align Sfile's technology with Peloton's Platform solutions, will enhance our clients' ability to access and analyze their operational data, improve decision making and optimize opportunities.
Sfile uses cognitive computing and machine learning to train bots and AI agents that autonomously mine unstructured data to accelerate and exchange advanced analytics. With Sfile, Peloton's Well Data Lifecycle Team realizes the opportunity to apply new approaches to two old challenges. First, how to best transform disparate unstructured data sets into structured and consistently coded information. Second, the application of data science techniques to the analysis of the data. The solution is to leverage Sfile's tools to mine the data, load it into our data platforms and apply advanced analytics to the data.
Fiona Hamilton, Vice President - Well Data Lifecycle Solution for Peloton, says, "Here is an opportunity to apply ML/AI to data loading and analytics for our products. A big win for our clients! A strategy to find, import and in some cases create the data to support their desired analysis."