Epiq adds Gen AI Text Summarization to Legal Workflow

Epiq has added Gen AI Text Summarization within the Epiq Service Cloud. This latest feature, powered by Azure OpenAI Service, is adaptable and scalable to support a wide range of legal processes, including eDiscovery and investigations, deposition summaries, mediations, and trials.

“Our Gen AI Text Summarization feature underscores Epiq’s commitment to making advanced technology accessible and practical for every legal professional without specialized AI knowledge,” said Eric Crawley, Senior Vice President, Legal Solutions at Epiq.

“This feature brings efficiencies to a diverse set of legal workflows while maintaining high standards of accuracy.”

The latest Gen AI advancement simplifies the review of complex documents to aid in early case assessment and enhance data analysis. Legal professionals can quickly locate and communicate key findings from large volumes of text, facilitating improved knowledge transfer for deposition and trial preparations. 

Concise, bulleted, or expanded summaries are available, and the ability to pin summaries for easy reference and export, along with key metadata into CSV format, extends its utility.

Gen AI Text Summarization will first be introduced in Epiq Discovery, an application within the Epiq Service Cloud, and a leading cloud-based SaaS solution supporting full matter lifecycle functionality. The controlled introduction of AI text summarization is available in the US, with a full release anticipated in Q3 this year.

Epiq will continue to introduce additional AI features this year including:

Prioritized Classification – this feature will classify documents by topic as a reviewer makes decisions, front-loading those most likely to contain key evidence for faster review, decreased cost, and quicker access to insights.

AI Chatbot – users will interrogate data with natural language in a conversational manner to receive answers from case data with citations to support evidence, accelerating fact-finding, and providing confidence in query results.