- May 10, 2023
- Gulfstream Legal
In last week’s blog, we introduced Relativity Active Learning Review and what users can expect throughout the five phases of an eDiscovery project where it has been employed. This week, we cover how active learning offers various options that can be customized to suit the specific needs of a case team. Some of these options include:
- Prioritized Review: This option feeds higher-ranked documents to reviewers first and is ideal when there is a need to quickly identify and review potentially relevant documents. It allows the review team to focus on the most important documents first, ensuring efficient use of time and resources.
- Coverage Review: This option feeds both high and low-ranked documents to reviewers, aiming to eliminate any gray area in the middle. It provides a balanced approach to review and ensures that all documents are thoroughly vetted, reducing the risk of missing relevant documents that might fall in the middle of the relevance spectrum.
- Customized Review Models: Relativity Active Learning Review allows for the creation of customized review models based on specific project requirements. These models can be tailored to the unique needs of a case, incorporating domain-specific or case-specific keywords, concepts or relevance criteria. Customized review models can significantly enhance the accuracy and efficiency of the review process, ensuring that only relevant documents are reviewed.
- Real-time Monitoring and Refinement: Relativity Active Learning Review allows the project manager to continuously monitor the progress of the review and refine the active learning index as needed. This ensures that the review is constantly optimized and yields the best results.
We recently released a case study that shows how legal teams can save significant time and money using active learning for review. Download it now.
In our next blog post on the topic of active learning, we’ll discuss why more case teams should use active learning for their project reviews.