Ringtail QuickCull speeds in-house ediscovery

August 28, 2009:FTI Consulting has announced the launch of Ringtail QuickCull, a new pre-configured hardware and software package for e-discovery.

With rapid deployment and out-of-the-box functionality, QuickCull enables corporations to cull and analyse data on-premise prior to review by outside legal teams, providing earlier insight into data and dramatic e-discovery cost reduction.

Upon installation, users can immediately begin indexing data and quickly identify duplicate files, which are automatically tagged for efficiency. Hidden files and columns, tracked changes and other modifications are also available to view.

Reviewers can search for documents using a variety of search methods, including keywords and complex Boolean queries that can also be restricted to specific metadata fields. QuickCull then presents documents for preview, allowing reviewers to mark and tag individual documents in preview mode. These markings are saved for export into processing, review and analysis tools via the EDRM XML standard, an industry standard which FTI helped to develop. QuickCull is also Unicode compliant to support international requirements.

The vast majority of data that corporations save and collect for e-discovery - whether in enterprise content management (ECM) systems, line of business (LOB) applications or other storage repositories - are not relevant to legal or regulatory matters. However, many corporations collect any and all data within the parameters of a case - all of the emails of ten key custodians, for example - and then work with their law firm or a legal service provider to facilitate processing and review. If the irrelevant data is eliminated earlier in the process, clients reduce the cost of not only of potentially extraneous processing, but also legal review by focusing on the data that matters to the facts at hand.

QuickCull users can index, search, cull and preview datasets within hours of collection without sending data off-site. In addition, QuickCull searches the data by a variety of methods, including keywords, data ranges and custodians, providing an early view into the likely responsive documents.

This enables in-house teams to understand the data better and earlier in the process, as well as providing significant strategic advantage.