Case Study: Global Energy Company slashes review costs by 94% and accelerates case strategy with OpenText Insight Predict

Energy and environmental tech company cuts review time by 60 percent with OpenText Insight Predict

A global energy company faced a fast-moving internal shareholder investigation alleging fraudulent and misleading securities statements and needed to review a growing collection of 540,000 documents on a tight 30‑day timeline. With only nine reviewers and shifting interview-driven priorities that introduced new custodians and documents daily, the client and its law firm required much faster, more flexible early case assessment to assess liability and prepare for interviews.

Using OpenText Insight Predict and Insight, the team created targeted filters and simultaneous review streams to prioritize topic- and custodian-specific documents, continuously incorporating new material. This approach narrowed the prioritized set, enabled focused subject-matter review, and used continuous active learning and sampling for high-recall review. After reviewing 10,000 documents the team reached 89% recall, finished the review in 12 days, eliminated more than 10,000 documents from human review, and realized a 60% faster review time and a 94% reduction in review costs while guiding case strategy.