TAR 1.0 or TAR 2.0: Which method is best for you?

In Casepoint, for example, a user can begin a TAR 2.0 session by reviewing as few as 50 documents (although our recommended ranking threshold is every 100 documents), and at each ranking threshold, the model re-ranks the corpus automatically. Doing this in tandem with Casepoint's Dynamic Batching feature, the user ensures that they are always looking at the highest-ranked documents. This allows you to strengthen your model faster because TAR 2.0 will continue to present documents in the batches until none of the documents presented are of relevance. Another benefit of TAR 2.0 is the ability to run multiple sessions simultaneously, where each session represents a different legal topic or issue you are trying to find relevant documents for. Being able to "bucket" groups of documents by relevant issues and have people dive into the review right away is a huge step forward.