Success storyIndustry• LegalSolution• OpenText™ Axcelerate™

Services• OpenText Professional Services

Results
Searched more than one million
documents augmented byanalytics, machine learning andProfessional Services
Achieved compliance with
document obligations pursuant
to government subpoena
Maintained lean teamand low costs

Pro bono case requires creativeuse of analytics

OpenText™ Axcelerate™ helps lean eDiscovery team prioritize
the review of more than one million documents“Using a continuous machine learning strategy
like what OpenText Axcelerate offers was, inmy experience, the most efficient and effective
option for this challenging matter.”Robert KeelingPartner
Sidley Austin LLPPro bono case requires creative use of analytics

The strategic eDiscovery team at Sidley Austin LLP are experts at
handling their clients’ litigation, investigation and compliance datachallenges. When one of their clients, a 501(c)(3) charity organization
with a fixed budget, received an unusual subpoena demand from thegovernment they deployed OpenText Axcelerate to prioritize andstreamline the review.
The Sidley Austin team leveraged analytics such as domain filtering,
communications mapping and custodian metadata to rapidly identify
and fast-track the review of relevant, low-risk content. This left the team
free to focus on nuanced attorney-client privilege analysis, augmented
by the Axcelerate Predictive Coding engine powered by continuousmachine learning. Each high-risk document was coded according toprivilege level, training a document model to (1) find more similar content
and (2) check the quality of privilege decisions across the production.
Using a combination of analytics and Predictive Coding, the SidleyAustin team satisfied the government subpoena while staying within abudget that would have been impossible with linear review methods.
Team size and project constraints
In this unusual case, Sidley Austin was retained to respond to broad
government subpoenas across 125 GBs of mailbox data. The charity
organization did not have an extensive internal eDiscovery capacity andrelied on the strategic eDiscovery team. And since every dollar spent on
the subpoena response was a dollar that couldn’t be used for providing
charitable services, the team handling the matter had to be lean—in
total there were about six attorneys—and had to rapidly identify theriskiest documents for priority review.

Efficient workflow with analytics and machine learning
The Sidley Austin team prioritized documents using Axcelerate
and a workflow that emphasized analytics and machine learning.
The firm chose OpenText™ Axcelerate ™ OnDemand, a managed
service that makes Axcelerate available for individual mattersand cases, supported by OpenText Discovery project managers.
Bolstering the team with a dedicated PM to help devise and run
search term queries, productions, and samples allowed the caseteam to focus on applying the nuanced legal judgments required for
responsiveness and privilege calls.
To start, the team narrowed the data using metadata filters. Knowingthat certain date ranges were outside the scope of the subpoena, theyrapidly filtered the dataset according to document creation date, sent
date and other time-based filters. Realizing that certain custodians andcommunications would trigger privilege, they further culled by domain
information. Throughout the process, Axcelerate’s visualized metadatafields displayed how many documents featured the metadata they wereseeking. To keep costs down, sampling was a must.
As the team interrogated their client’s data, they experimented
with keywords and ran samples out of the larger responsive sets todetermine whether the keywords were targeted or burdensome. They
were able to rapidly evaluate huge datasets to determine whether they
were valuable for review. Samples that returned rich results were fasttracked into a review workflow, which was aided by Predictive Coding.
The Predictive Coding algorithm created a data model that suggested
similar documents for review. And, since Axcelerate Predictive Coding
is issue-based, they were able to simultaneously train the system toquality check their privilege decisions. Decisions that the computer
disagreed with could be quickly identified for second pass review.

“The challenge was a
mailbox request forover a million documents
and a small team. How doyou produce that many
documents without
the ability to do a
linear review while
protecting privilege?”
Ray Mangum

Associate
Sidley Austin LLP

About OpenText

OpenText, The Information Company™,
enables organizations to gain insight
through market leading information
management solutions, on-premises orin the cloud. For more information about
OpenText (NASDAQ: OTEX, TSX: OTEX)
visit opentext.com.
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