Case Study: Acorn Legal Solutions achieves 90% responsiveness accuracy and restores confidence in TAR with Reveal's NexLP AI

Acorn Legal Solutions - Customer Case Study

Acorn Legal Solutions, representing a boutique litigation client, faced a complex set of non-searchable medical documents with inconsistent OCR and overlapping language that made it difficult to differentiate documents by sender and left the team skeptical of traditional TAR. To address the challenge, Acorn engaged Reveal and its AI tools—Reveal's NexLP AI (StoryEngine)—to evaluate automated review on the matter.

Reveal deployed NexLP's AI/StoryEngine, using entity extraction, a coverage queue, and improved prediction models to identify documents by sender and predict responsiveness in a human-like way. The solution stabilized quickly despite no metadata and achieved 90% responsiveness accuracy after only 2,000 coded documents (compared to ~50% for the next closest competitor), restoring Acorn’s confidence in TAR and producing trained models reusable for future matters.

Acorn Legal Solutions

Lia Majid

Chief Executive Officer