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Pharma Review with Thousands of Emails Processed with Blackout

The Challenge

A Milyli customer was headed into litigation with 20 million records. This pharmaceutical case included mostly email files needing standard threading. While there was plenty of time to process these documents, the customer expressed concerns about meeting their high standards for a timely, quality review. They also did not want to waste their approved billing hours TIFFing Excel files.

 

Additionally, this job called for inverted redactions due to its enormous size – something very common in pharma litigation. Inverted jobs are used when it is easier to redact a majority of the information found in a document and un-redact (inverse) the product data in question. In this case, the review called for redactions on everything except the information related to relevant drugs involved in the case.

Key

Facts

  • 20 Million Records

  • No TIFF-ing

  • Need for Inverted Markups

The Solution

Accuracy cannot be overlooked and Blackout’s optical character recognition technology provides the highest level of precision for Relativity users who need to mark up or redact image-based documents. This was pivotal to many of the email files saved as PDFs and images.

 

Blackout’s ability to process and redact native Excels expedited the review and allowed the team to deliver produced documents early. When placing manual redactions in large Excel files with Blackout, it is possible to redact entire rows and columns in a single operation – compared to images of Excel files where rectangles must be drawn on multiple, nonconsecutive image files. In this case, the Blackout users remained ahead of schedule, even after including additional quality passes the client requested.

 

This customer specifically found Blackout’s external redaction workflow advantageous for viewing large Excel files. This is because Relativity’s viewer cannot view those files. With Blackout, they were able to manually redact documents in Excel and upload those files back into Relativity without losing the original native version.

Information Blackout Can Flag

  • Personal Identification Numbers

  • Account IDs

  • Credit Card Numbers

  • Dates

  • Contact Information

    • Emails​

    • Phone Numbers

    • Addresses

  • Charts

  • Pivot Table Data

  • Embedded Objects

  • Notes/Comments

And much more.

Blackout uses regular expression (regex) text strings to find terms in documents that match the regex pattern so that they may be marked up, including the ability to redact or markup partial words and phrases. The user’s review team writes these with or without Milyli's assistance and can load them directly into Blackout or import them in bulk.