What is the AI eDiscovery process?

eDiscovery is the process of finding, preserving, and producing electronically stored information (ESI) for litigation or investigations. An AI-assisted process follows the familiar stages of the Electronic Discovery Reference Model (EDRM) but applies machine learning and language models to reduce the manual work at each step.

A typical AI eDiscovery process runs through these stages:

• Identification and preservation: map where relevant data lives and issue legal holds so nothing is lost or altered.

• Collection: gather data from email, chat, file shares, and other systems in a forensically sound way.

• Processing: de-duplicate, filter, and normalize the data so it is ready to review, using analytics like near-duplicate detection and email threading.

• Review: the stage where AI has the biggest impact. Predictive coding ranks likely-relevant documents first, classification models flag privilege or sensitivity, and summarization and fact extraction help reviewers understand long records quickly.

• Production: deliver the responsive, non-privileged documents in the agreed format with metadata intact.

Adding AI is not about removing human judgment but focusing it. Reviewers spend less time reading irrelevant material and more time on the documents that matter, while a complete audit trail keeps the process defensible. Validation steps, such as sampling to measure precision and recall, help confirm the AI is performing as expected before you rely on its results.

For a fuller walkthrough of where AI fits at each stage, see How AI Fits into Modern eDiscovery.

Claira is an AI eDiscovery platform that applies classification, summarization, and fact extraction across the review stage to cut manual hours while keeping reviewers in control. See how it works.