Case Study: Phillips Lytle LLP achieves rapid, AI-driven review of 600,000+ documents in two weeks with OpenText Axcelerate

Phillips Lytle makes innovative use of AI to expedite legal review

Phillips Lytle, a national law firm with a dedicated eDiscovery and Digital Forensics group led by partner Anna Clark, was asked to review a large discrimination matter that began with over three million documents and was culled to roughly 600,000. Mid-review the timetable compressed from months to just weeks, making a traditional linear review infeasible and forcing the team to find a faster, defensible approach.

Working with OpenText Discovery and Professional Services, Phillips Lytle used OpenText Axcelerate’s continuous predictive coding, statistical sampling, and repurposed review decisions (~5,000) to train the model iteratively, then bucketed and auto-categorized the corpus for prioritized review. The hybrid TAR workflow automated review of over 500,000 documents, produced validation showing 99.5% accuracy (less than 0.5% miscategorized), enabled a defensible stop, met the two-week deadline, and substantially reduced staffing and review costs.

Phillips Lytle LLP

Anna Mercado Clark

Partner