PILYTIX

Software DevelopmentTexas, United States11-50 Employees

Many organizations use CRM analytics as an active part of their sports sales strategy and/or for university fundraising support. To maximize productivity among sports and fundraising teams, PILYTIX is a technology company that uses artificial intelligence (AI) and machine learning (ML) to generate pipeline analytics. In doing so, revenue generating teams will make more money, faster. 

Great AI and ML tools learn from historical patterns of data and compare those patterns to current data to give insights about most likely outcomes. PILYTIX combines a sophisticated implementation of AI and ML, with a unique philosophical shift in thinking about the revenue generation process that creates customer-centric predictive analytics results in a process for leaders to have more accurate sales pipeline forecasting. PILYTIX benefits every level of revenue generating activities on a daily basis, taking into account ever-changing customer data and its impact on sales, fundraising, and retention. 

Our customized tools provide sales and fundraising teams with deep, actionable insights, allowing teams to focus on the right customers at the right time - with a clear understanding of factors that move customers through the pipeline faster. PILYTIX’s unique sales and fundraising technology takes the guesswork out of revenue forecasting, reducing reliance on “gut feelings” as the basis for sales and fundraising follow up. Using “explainable” AI to ensure that end users understand exactly how the output is generated, teams are positioned to make smart decisions that maximize revenue generation.

PILYTIX also enhances data management strategies among those companies that need to aggregate multiple, disparate data sources. PILYTIX provides a virtually frictionless system used for joining big, cumbersome, constantly evolving datasets and derives timely, usable insights via a unique data environment that provides a nimble approach to ingesting, centralizing, and transforming data.

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