Verbotics AI
Bill Schieffelin is a seasoned professional with extensive experience in sales and business development, particularly within the legal and technology sectors. Currently serving as the Head of Sales at Verbotics AI since January 2020, Schieffelin focuses on leveraging clinical AI for legal terminology standardization and workload reduction. Prior to this role, Schieffelin held key positions at Servient, Inc. as Vice President of Strategic Alliances, and Counsel on Call as Vice President of Business Development, where emphasis was placed on e-discovery and data management solutions. Additional experience includes senior roles at SPI Technologies and Thomson Reuters, underscoring a strong background in sales leadership and strategic alliances across various companies. Schieffelin holds a Juris Doctor from The University of Texas School of Law and a Bachelor of Arts from Baylor University.
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Verbotics AI
Conventional healthcare NLP engines are overly dependent on clinical terminologies for identification of essential concepts in physician narratives. Accordingly they fail to fully capture all aspects of every medical condition, diagnosis, and procedure documented by physicians. Absent this requisite information the output often contains many non-specific, non-actionable results. Verbotics is a proprietary, first-of-its-kind healthcare NLP engine that normalizes free-flowing patient data to the most exacting clinical concepts available. Extracting socio-economic indicators of health, major/minor complications, allergies and risk factors, Verbotics then transforms unstructured patient information into a timeline of clinical events enabling a variety of use cases. Our Solution Verbotics is a fully proprietary healthcare platform with no third party or open-source components. Verbotics intuitively understands patient data, both structured and unstructured, incorporating all patient information, regardless of format. This heretofore unobtainable data is transformed to overcome long standing challenges in optimizing reimbursement, improving clinical documentation, automating coding audits, and improving quality metrics and population health analytics.