Review Acceleration through Intelligent Document Prioritization
Using results from active learning, communication analysis, keyword searching and other queries performed in Relativity, LayerCake™ learns which documents you like the most and which documents can be suppressed from review.
In LayerCake™ lingo, each query or analytics result fed into the LayerCake™ engine can be thought of as a layer. As users submit layers, LayerCake™ becomes increasingly proficient at distinguishing between responsive and non-responsive documents, updating document priority tier rankings automatically. These rankings can then be used to accelerate review, promote key documents, suppress non-responsive documents from the set and uncover hidden pockets of data.
Use LayerCake™ to:
- Calculate a single, all-inclusive priority tier ranking for each document based on results across analytics features and document retrieval methods
- Input results from active learning, communication analysis, keyword searching, clustering and timeline analysis
- Reduce the total number of documents requiring review
- Detect relevant documents faster