This is like giving every litigation team a super-fast junior attorney that can read thousands of documents, flag what’s relevant, explain why it thinks so, and show its work—so humans can make final calls much faster and with better evidence at hand.
Traditional document review in litigation and investigations is slow, expensive, and error-prone because humans must manually read huge volumes of emails and files. AI-assisted review reduces the volume of documents needing full human review, prioritizes the most important material, and provides rationales and confidence scores so lawyers can defend their decisions in court or to regulators.
Deep integration into legal e-discovery workflows and Relativity’s existing platform, plus access to large volumes of labeled legal-review data that can continuously improve models and make switching costly for established legal teams.
Hybrid
Vector Search
Medium (Integration logic)
Context window cost and latency for large document sets, along with legal-data privacy and on-prem/tenant-isolation requirements.
Early Majority
Focus on explainable AI review—rationales, citations, and scores tightly embedded in existing Relativity e-discovery workflows, aimed at defensible legal outcomes rather than generic document summarization.