What is statement-of-fact extraction in eDiscovery?

In litigation and investigations, the facts that matter are scattered across thousands of emails, chats, and documents. Statement-of-fact extraction is the use of natural-language AI to identify and pull out discrete factual assertions - an action, the people involved, and the date or time it happened - from each document.

Instead of a reviewer reading every record to note what occurred, the AI surfaces structured facts that can be sorted into a timeline. This supports several common tasks:

• Building case chronologies from large document sets.

• Identifying key events, admissions, and inconsistencies.

• Prioritizing which documents a human should review first.

• Preparing witness outlines and case summaries.

Good extraction keeps each fact linked to its source document so it stays verifiable and defensible, and it flags uncertainty rather than guessing. The goal is not to replace legal judgment but to get reviewers to the relevant facts faster.

Claira applies fact extraction across review sets so teams can move from raw documents to a working chronology in less time. Explore Claira.