Our Team

Eric McKim - Chief Executive Officer (CEO)


MBA,CISM,CGEIT,CRISC,CISA,ITIL



Eric is the Chief Executive Officer of Knowledge Analytics. In this capacity, Eric creates, communicates, and implements KAI's vision, mission, and overall direction. He leads the development and implementation of KAI's overall strategy. Eric is a recognized industry enterprise and technical architect specializing in information security and privacy. He has over 17 years of experience designing, implementing and leading highly visible enterprise security and technical solutions for both commercial and federal Government organizations. Much of this experience is in health care, financial services, federal civilian government and DoD. Eric has led the implementation of complex Service Oriented Architectures (SOA), Cloud, Big Data/Analytics, Smart Grid (Utilities) and Satellite system security architectures. Eric has a MBA from John's Hopkins University. He is also a Navy veteran.


John McKim - Chief Technology Officer (CTO)


MS,CISSP, AWS Solution Architect, AWS Developer, AWS SysOps, Cloud+, Security+



John is the Chief Technology Officer (CTO) at Knowledge Analytics. In this capacity, he oversees current technology and creates relevant policy that aligns technology related decisions with KAI's Goals. He is responsible for technically incorporating intelligent behavior via Artificial Intelligence and Big Data Analytics into various domains such as Health Care and Fraud Detection. John has over 35 years of experience in enterprise architecture, software architecture, design, and implementation of sophisticated enterprise systems at NASA, DoD, and other federal agencies. He was the project lead and chief architect on several successful NASA projects at the Goddard Spaceflight Center, Enterprise Architecture gigs at DISA, MHS, and NIH, as well as an expert designer and coder. John's primary interests are in the development of intelligent systems that perform intelligent decision support, data analytics, data mining using rule engines, statistical analysis (regression), and data mining. He has also focused on information modeling and ontologies as they can be apply to interoperability and enterprise architectures, as well as building tools that allow these models to be easily incorporated into the enterprise.