Customer stories

Leading Law Firm

Pro bono case requires creative use of analytics. OpenText™ Axcelerate™ helps lean eDiscovery team prioritize the review of more than one million documents

Challenge

  • The challenge was a mailbox request for over a million documents and a small team. 

Results

  • Searched more than one million documents augmented by analytics, machine learning and Professional Services

  • Achieved compliance with document obligations pursuant to government subpoena

  • Maintained lean team and low costs

Story

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 continuous machine learning.

Woman working on laptop with scales of justice in foreground

Using a continuous machine learning strategy like what OpenText Axcelerate offers was, in my experience, the most efficient and effective option for this challenging matter.

Robert Keeling
Partner, Sidley Austin LLP

Each high-risk document was coded according to privilege 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 Sidley Austin team satisfied the government subpoena while staying within a budget 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 and relied 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 the riskiest documents for priority review. 

The challenge was a mailbox request for over a million documents and a small team. How do you produce that many documents without the ability to do a linear review while protecting privilege?

Ray Mangum
Associate, Sidley Austin LLP

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 matters and 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 case team to focus on applying the nuanced legal judgments required for responsiveness and privilege calls. 

To start, the team narrowed the data using metadata filters. Knowing that certain date ranges were outside the scope of the subpoena, they rapidly filtered the dataset according to document creation date, sent date and other time-based filters. Realizing that certain custodians and communications would trigger privilege, they further culled by domain information. Throughout the process, Axcelerate’s visualized metadata fields displayed how many documents featured the metadata they were seeking. 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 to determine 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 to quality check their privilege decisions. Decisions that the computer disagreed with could be quickly identified for second pass review.

About Leading Law Firm

The strategic eDiscovery team at Sidley Austin LLP are experts at handling their clients’ litigation, investigation and compliance data challenges. When one of their clients, a 501(c)(3) charity organization with a fixed budget, received an unusual subpoena demand from the government they deployed OpenText Axcelerate to prioritize and streamline the review.