OpenText
1807 Case Studies
A OpenText Case Study
Sidley Austin LLP’s strategic eDiscovery team was retained pro bono by a 501(c)(3) charity facing a broad government subpoena that encompassed roughly 125 GB of mailbox data and more than one million documents. With only about six attorneys available and strict budget constraints—every dollar spent reduced the client’s charitable services—the team needed a fast, defensible way to identify high-risk documents and protect privilege without resorting to costly linear review.
The firm used OpenText Axcelerate OnDemand with support from OpenText Professional Services, applying metadata and domain filters, communications mapping, targeted sampling, and continuous machine‑learning Predictive Coding to prioritize review and quality‑check privilege decisions. This approach enabled the team to search and triage over a million documents, meet subpoena obligations, and keep the review lean and cost‑effective.
Ray Mangum
Associate