Case Study

Deep Experience in Large Scale Data Management

KeyLogic leaders have served on the US National Academy of Sciences Board of Research Data and Information and have been the Secretary General of CODATA (Committee on Data) under the International Science Council. We have supported two US White House Interagency Working Groups in Informatics and Digital Data. KeyLogic data policy experts pay particular attention to data …

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Data Science for an Improved Carbon-Capture Process

KeyLogic develops process simulation flowsheets and applies data science tools, such as uncertainty quantification, design of experiments, and ML, to help design better carbon-capture processes. Our work reduces the time and cost to maximize learning from experiments in pilot plants. In addition, we support the modeling and analysis of low viscosity, water-lean solvents with polarity swing regeneration that …

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Fraud Detection Using Advanced Analytics

Working for the government with a major credit card company, KeyLogic designed a set of fraud detection data mining modules (KeyDetectTM) that use artificial intelligence to identify potential cases of fraud while a compliance module detects suspicious credit card transactions. Users are provided an easy-to-use dashboard that allows them to build customized data displays to fit their particular needs. Managers …

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Carbon Capture Simulation for Industry Impact

KeyLogic data scientists and subject matter experts support the analysis and optimization of carbon capture technologies. We work with national laboratories, industry, and academic institutions to apply cutting-edge computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. 

KeyPerform leads to improvements at the Department of Labor

KeyPerform enabled us to improve the Department of Labor’s Capital Planning and Investment Control (CPIC) processes.  In the support of the DOL OCIO’s Control Reviews of IT investments, we advanced the process from one that was unstructured, subjective, and variable to one that is more structured, objective, and repeatable. 

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