digIT™ Enterprise
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The second largest uncontrolled cost in business outside of healthcare is the collection, preservation, review and production of data in litigation.

Fact is that more than 90% of business documents today exist in digital format. What this means is the vast majority of discovery involves more electronic data than paper. This exponential growth of electronic data has created an enormous challenge for legal and IT teams who have a need to quickly identify custodians of interest, determine how much data each custodian owns and where that information is located. The not-so-good news is that the amount of information to search during discovery will not diminish anytime soon. The good news is that there is technology available today that meets this challenge head on.

Designed specifically to address the challenges faced by legal and IT teams during discovery, digIT Enterprise is a software application that, once deployed within an enterprise, allows the ability to search, collect and preserve all electronic files stored on your network. This includes E-mail with attachments, spreadsheets, word processing documents, voice mail messages, databases, Instant Message files, and foreign language documents - essentially, any type of file that could have bearing on your case. This not only streamlines the collection and preservation of evidence, but also dramatically reduces the costs compared to those you may have incurred in the past.

Tradition versus Technology

Many corporations today, when served with a subpoena, have standard practices that include arranging for in-house lawyers and / or outside counsel and IT to mirror the hard drives of primary custodians, once interviewed. This practice, though common, causes loss of valuable time, over-collection of data, and unnecessary hours billed for review of huge collections of information unrelated to the investigation. With the application of digIT, custodians may be automatically identified; only information related to the matter is collected and preserved, resulting in a much smaller percentage of data that requires further analysis. Less time, less data, less review time, lower costs.
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