Capital One Services, LLC

Rapidsos, Inc.

Leah Lewy

Alberto Silva

James Patrick Olejar

Conor Fucci

Rohan Mehta

Anthony Shewnarain

Steven Freeman

Stephen Jurcsek

Ross Arkin

Minnie Virk

An emergency response data system (ERDS) provides artificial intelligence (AI)-based emergency notifications to operations centers using radio-based dispatches from emergency communications center (ECC). The ERDS receives audio data of a radio-based dispatch of first responders to a location of an initiated emergency communication. The ERDS provides the audio data to an AI model with a prompt to transcribe the audio data into a radio dispatch transcript. The ERDS provides the radio dispatch transcript to the AI model with a prompt to analyze the radio dispatch transcript to extract a location of the initiated emergency communication from the radio dispatch transcript. The ERDS provides an AI-based emergency notification to an emergency response application that is operable to display the AI-based emergency notification on an operations center computing system. The AI-based emergency notification includes the location of the initiated emergency communication.

Systems and methods of providing emergency notifications to operations centers using radio-based dispatches

Systems and methods for dynamic detection of security features based on self-supervised natural language extraction from unstructured data sets are disclosed. The system may receive an unstructured data array including a full text of financial narrative. The system may serialize the unstructured data array to form one or more first data arrays including portions of the full text as discrete financial risk narratives. The system may build a tokenization dictionary and determine condensed summaries for each portion of the full text. The system may determine a relevancy score and a sentiment score for each condensed summary and calculate an overall relevancy score as a weighted average of the relevancy score and the sentiment score. When the overall risk score exceeds a predetermined threshold, the system may execute one or more security actions.

Systems and methods for determining financial security risks using self-supervised natural language extraction

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Jersey City, NJ, United States of America

Leah Lewy