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Company Name

RankMiner Predictive Voice Analytics

Year Established







St. Petersburg, FL

Amount Raised

$1MM to $2MM

Supporting Documents





RankMiner’s patented A.I. platform analyzes a person’s voice – not the words used, but HOW they are spoken – to reveal speaker intent and predict what that speaker is likely to do. Our clients realize performance improvements ranging from 20% to over 100% by reducing their costs of Employee turnover and increasing revenue from Collections and Cross Sales. RankMiner’s patented technology extracts hundreds of paralinguistic features, such as energy, intensity, happiness, anger, etc. from each phone conversation and correlates them to specific business outcomes to deliver material performance improvements by predicting employee turnover, customer sales and collections. We take a fundamentally different approach than other call analytics in the market. Our purpose is to understand speaker intent and predict what that speaker is likely to do. We start with the goal of that prediction first: • What do our clients want to see more of? Greater customer spend? Increased payments? • What does do they want to see less of? Lower employee turnover? Lower customer churn? RankMiner can be applied anywhere there are observable conversations.

Company Leadership

Preston Faykus

Founder & CEO

Founder & CEO RankMiner Predictive Voice Analytics | BA, University of Texas | MBA, University of Chicago. Prior to RankMiner, Preston served as SVP of Fraud Analytics at FIS, where he ran a 650-employee division, and grew revenue by 250% and increased margins by 40%. Preston’s 17 years of FinTech experience include helping create DialogBank’s consumer banking division in Russia and leading emerging technologies at EuroNet Worldwide, an electronics payment organization.

Erik Hammel

Technical Co-Founder

Technical Director RankMiner Predictive Voice Analytics | 5 advanced degrees | Ph.D. Mathematics, Rensselaer Polytechnic Inst. Erik earned his Ph.D. in Applied Mathematics specializing in decision science, stochastic optimization, dynamic programming, and reinforcement learning. Erik is a developer focused on data science and machine learning. Previously, Erik served as Systems Engineer at General Dynamics focusing on ballistic missile defense and radar systems.

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