OpenText Legal Knowledge Management

OpenText™ Legal Knowledge Management is an enterprise solution designed to support legal professionals in locating, organizing, and analyzing large volumes of structured and unstructured data. It provides a unified search interface that connects to multiple enterprise systems, enabling more efficient knowledge reuse and decision-making.

Key features and functions include:

Predictive search
Utilizes OpenText MindServer to deliver concept-based search results using AI-powered concept analysis and supervised machine learning, identifying relevant content beyond exact keyword matches.

Classification
Automates the tagging and categorization of documents using customizable rules to support organization and retrieval.

Concept group search
Uses machine learning to cluster related content, revealing connections and themes that may not be evident through standard search techniques.

Data visualization
Presents search results in graphical formats, organized by content and metadata, to help users identify patterns and insights more easily.

Text-mining integration
Automatically filters large volumes of documents to help surface legal knowledge insights.

Secure integration and single sign-on
Provides secure access to enterprise information systems, including Microsoft SharePoint and OpenText Legal Content Management.

The platform is designed to connect to data across an organization's disparate systems, including document management, billing, matters, dockets, emails, file shares, intranets, and portals, and supports use cases such as classifying incoming data, identifying subject-matter experts, supporting new-business pitches, and informing case strategy.

This solution was formerly known as Decisiv Search.  It was orginally developed by Recommind which was aquired by OpenText in 2016.