Story Engine 2.21 Release: Custom Entities Uncover Signals, Risks & Relationships Within Data

Today’s legal and corporate compliance and risk managers require technology that can mine data faster and more effectively than manual review can achieve.  In the latest release of NexLP’s Cognitive AI platform, Story Engine, users can get the most out of their data with the ability to create custom entity types, as well as enhance entities already built within the platform.

This groundbreaking capability empowers NexLP customers to teach the platform new terms that are specific to a corporation or legal matter and seamlessly activate it with any AI Model through the AI Model Library without any code or technical knowledge. Custom entities can be used to:

  • Enhance the platform’s ability to understand the relationships between terms typically ignored by most NER platforms, since they aren’t trained by default on domain specific concepts but rather real world concepts. 

  • Quickly find sensitive data, that pattern-based searches (e.g. RegEx) typically miss, like addresses (PII), medical conditions (PHI), educational records (FERPA) or proprietary intellectual property.

  • Uncover potential areas of compliance risk or problematic behavior by teaching the system about specific competitors, partners, products or government officials.

  • Gain actionable insights from your “Voice of the Customer” data captured via reviews and surveys where product names, services or account numbers are mentioned.

  • Extract occurrences of custom entity terms for use in Data Breach review, Due Diligence, Regulatory Compliance and Voice of the Customer analysis.

Collectively, these features provide users the ability to detect patterns and anomalies, map custodian relationships and conversations and spot behavioral indicators at the speed and scale needed. Understanding domain specific concepts is critical for an enterprise AI platform because meaning is driven by context. Context can only be accurately understood if the AI is taught that the term is important, in the context in which it is used. Users can simply highlight examples of the term(s) in use and the platform will automatically learn from there. 

VIDEO: TAKE A LOOK INSIDE A REAL-WORLD USE CASE FOR STORY ENGINE 2.21

Additional Release Enhancements:

  • Improved document highlighting quickly allows users to identify examples of custom entity terms or phrases directly in documents to apply for searches later.

  • Run search term reports to identify documents containing specific keywords or strings.

  • Use search term reports to quickly understand holistically what’s in your data set, or drill down into documents to understand their context and identify key documents.

  • Importing document tags into Story Engine with enhanced interface.

  • Users have more control over their storybook with optional new Storybook Administrator permission toggle.

  • Speed up processing performance by enabling only the analysis important to your matter.

  • Improve TAR workflows by informing the learning system of important entities and domain specific concepts. This allows our COSMIC active learning system to make better decisions on the documents that are important and not important to your matter.

Jay Leib

Jay Leib is the CEO of NexLP, Inc. Jay has successfully founded and led software start-ups throughout his career. Most recently, Mr. Leib was at Chicago-based Relativity (formerly kCura) as the Chief Strategy Officer. Relatiivity is a Chicago based company focused on the eDiscovery vertical.