Reed Smith cuts document review costs by $2.3M+ with Relativity aiR
Reed Smith deployed Large Language Models & Generative AI for E-Discovery & Document Review in Law Firms. As reported by www.contextwindows.ai: $2.3M+ review cost savings.
Source-reported figures — cited source: www.contextwindows.ai
What Reed Smith was trying to fix
Reed Smith's first-pass document review at scale required broad coverage and large reviewer teams, driving up cost and timeline on high-volume litigation, investigation, and data subject access matters where document populations routinely reach millions. Traditional TAR (technology-assisted review) scored chat messages too low, causing key evidence to slip through review.
What Reed Smith deployed
Reed Smith deployed Relativity's aiR to screen documents on first-pass review, using AI to review and prioritize documents — including chat messages — ahead of human reviewer teams. Using aiR on first-pass review has become a standard step in the firm's workflow for matters involving client data.
Results
The aiR-driven review saved Reed Smith over $2.3M in review costs, cut review time by 11,300 hours, and reduced the document population requiring review by 500,000 documents. The AI screening also surfaced all three key documents that opposing counsel used in a deposition, catching evidence that prior TAR chat-scoring had missed.
Key Takeaways
- AI first-pass screening surfaced deposition-critical evidence that traditional TAR scoring of chat messages missed.
- aiR has become a default first step for first-pass review on matters involving client data, not a one-off pilot.
Evidence for Reed Smith's E-Discovery & Document Review deployment
- Reported outcome metrics
- 3 cited below
- Cited source
- www.contextwindows.ai
- Last updated
- Source published
- Source link checked
Explore Related
Details
- Industry
- Law Firms
- Use Case
- E-Discovery & Document Review
- AI Technology
- Large Language Models & Generative AI
- Company Size
- Enterprise
- Company
- Reed Smith
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