Success story
Stinson Leonard Street LLP
Industry• Legal, Professional ServicesSolution• OpenText™ Axcelerate™

Services• OpenText Professional Services

Stinson Leonard Street LLP efficiently
and rapidly analyzes a large, classaction production set

OpenText™ Axcelerate™ provides cutting-edge Predictive Coding technology toidentify critical case documents after reviewing only 2.3% of production set
Results
Reduced review costs by 97.7%
through AI-powered, prioritized
review workflow
Achieved earlier case insights
with Predictive Coding andadvanced analytics
Completed project in amanaged environment without
long-term commitment“With the massive number of documents produced in modern
litigation, it is too costly to try to review every document
produced. With OpenText, we have been able to focus on thesmall percentage of documents that actually matter.”Bill Greene

Partner
Stinson Leonard Street LLPStinson Leonard Street LLP efficiently and rapidly analyzes a large, class-action production set

Stinson Leonard Street LLP, a 500+ attorney law firm based in theAmerican Midwest, represented a defendant in a large class action
matter. The case team needed to review a production of 1.3 million
documents to inform their strategy on behalf of their client. WithOpenText, the team leveraged advanced analytics and machinelearning capabilities to expedite insight findings and avoid thedaunting labor costs of a linear review.
The case team selected OpenText™ Axcelerate™ OnDemand, hosted andmanaged by OpenText Professional Services, to enhance their review
efficiency. Suspecting that there would be a high concentration of
produced documents that were not ultimately useful for their litigationstrategy, the team identified the important documents faster using
Axcelerate’s analytics and machine learning capabilities.

Faster case insights

First, the case team performed an initial sample, gathering a small
subset of documents and reviewing them to establish a baseline ofrelevancy. Next, they conducted some basic culling using Axcelerate’s
Smart Filters, Phrase Analysis and keyword searching toolset to reducethe document volume further.
The team then created an input set of documents to begin training
Axcelerate Predictive Coding technology, and ran several iterative
cycles for machine learning. In each iteration, Axcelerate recommended
a priority batch of documents for review, and the team further refined
the solution’s training. The review was completed when the team wassatisfied, based on the analysis performed, that it had identified thecritical documents needed to inform their strategy. To validate, theteam analyzed a small sample of the unreviewed content to verify that
nothing significant was missed.

Lower review costs

Bill Greene, the partner overseeing the project, commented, “With themassive number of documents produced in modern litigation, it is
too costly to try to review every document produced.”
Using Axcelerate’s advanced analytics and Predictive Coding, thereview team located the critical documents upon reviewing only 2.3
percent of the total document set, fewer than 30,000 of the 1.3 million
documents they received.
“We were very pleased with the efficiency and overall cost savingsof OpenText Axcelerate OnDemand,” said Greene.

Better results

By leveraging a small, knowledgeable team of just three attorneys, thefirm kept the review process consistent and efficient, while developing asubstantive understanding of the case facts in real time.
“When document review is concentrated with a small group who areknowledgeable, you get to the relevant documents more quickly.
With Predictive Coding, we have been able to focus on the small
percentage of documents that actually matter,” Greene concluded.

“We were very pleased
with the efficiency andoverall cost savings ofOpenText Axcelerate
OnDemand.”Bill GreenePartner
Stinson Leonard Street 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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