The whitepaper explains how advancements in AI are revolutionizing document review by refining responsiveness in single matters, enabling work product reuse across multiple cases, and providing portfolio-level analytics for strategic decision-making. Unlike outdated TAR models, modern AI uses NLP and layered learning to capture context, reducing irrelevant documents and review costs. Real-world examples include cutting 430K documents in a Second Request, reusing privilege and redaction coding across cases, and achieving a 90% privilege review set reduction for a global tech company. These applications deliver speed, accuracy, and significant cost savings.

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