Technology Assisted Review (TAR) is a way of handling the review phase of eDiscovery by deploying algorithms that can classify documents based on input from expert reviewers. It can provide statistics, categorization, and reporting data that is superior to human-only review.

There are two general variations of TAR:

• • TAR 1.0, also known as “predictive coding,”
  • TAR 2.0, also known as “continuous active learning.”

With both versions, the subject-matter expert trains the algorithm, which then follows a defensible workflow to make relevancy decisions in a consistent, cost-effective manner.