Case Study: H&A eDiscovery achieves rapid 235,000‑document review in four weeks with Relativity's active learning

Used Active Learning in Relativity, Allowing a Four-person Review Team To Produce 235,000 Documents in Four Weeks

H&A eDiscovery faced a high‑stakes e-discovery challenge: a Canadian law firm needed 730,321 documents reviewed in just four weeks with a four-person review team. To accelerate the process, H&A eDiscovery employed active learning in Relativity to prioritize and surface the most relevant documents.

Relativity’s active learning workflow was run after H&A excluded 86,586 non-inclusive or non-searchable items; the system learned reviewers’ coding decisions and reprioritized the review queue, enabling the four-person team to produce 235,000 reviewed documents in four weeks — a clear, measurable boost in throughput and review efficiency using Relativity.

H&A eDiscovery

Lynne Brigant

Director of Client Services