MANAGED REVIEW, AI REVIEW & ACTIVE LEARNING
Review Workflows Built for
Speed, Accuracy, and Defensibility.
CDS combines experienced lawyer-technologists, AI-powered review workflows, and proven Active Learning methodologies to help legal teams review faster, reduce costs, and maintain defensibility. Whether deploying traditional managed review, Relativity aiR, or Continuous Active Learning, every workflow is designed around quality, transparency, and measurable outcomes.
Scalable Review Teams Backed by Proven Operational Discipline
CDS provides end-to-end Managed Review services that combine experienced review managers, attorney reviewers, structured quality controls, and technology-enabled workflows. Every engagement is tailored to the complexity of the matter while maintaining transparency, defensibility, and predictable project execution.
Blind Competitive Review
CDS outperformed another provider by delivering lower overall review costs, significantly higher review pace, and reducing the privilege population through revised searching strategies.
| Cost | 30% Lower |
| Review Pace | Higher Productivity |
| Privilege Population | 31% Reduction |
Opioids MDL
CDS managed review operations at enterprise scale while maintaining defensible workflows and accelerating review timelines under demanding litigation deadlines.
| Review Team | 180 Reviewers |
| TAR Recall | 80% |
| Search Turnaround | Weeks → Days |
Flexible Review Services Across Every Stage of Discovery
CDS assembles review teams around the needs of each matter, combining experienced attorney reviewers, technology specialists, and structured management practices to support everything from targeted privilege reviews to enterprise-scale productions.
Document Review
Responsive and relevance review supporting productions of every size while maintaining consistency across reviewer teams.
Privilege Review
Structured privilege identification, quality validation, and privilege log preparation designed for defensible production.
Issue Coding
Coding strategies aligned to case themes, witness preparation, chronology development, and litigation analysis.
Technology Assisted Review
Integration with Active Learning and AI Review workflows to reduce manual effort while maintaining defensibility.
Specialized Review
Foreign language reviewers, subject matter experts, and industry specialists available as project requirements evolve.
Production Readiness
Final quality validation prior to production including privilege verification, sampling, and production support.
Review Teams That Adapt to Your Matter
Every organization approaches document review differently. CDS supports multiple engagement models that integrate seamlessly with existing legal teams, litigation support professionals, and outside counsel.
Fully Managed Review
CDS manages staffing, workflow administration, reporting, quality control, and production from project kickoff through completion.
Hybrid Review Teams
Client attorneys focus on strategic review while CDS manages high-volume responsiveness, privilege review, and day-to-day review operations.
Overflow Review Support
Scale existing review teams quickly during discovery peaks without disrupting established workflows or production schedules.
Specialized Review Teams
Deploy experienced reviewers for technical content, multilingual review, investigations, or highly specialized legal subject matter.
Disciplined Review From Planning to Production
Every engagement follows a structured methodology that balances speed, quality, and defensibility from kickoff through final production.
Plan
Strategy & review design
Staff
Assemble review team
Review
Responsive document review
Validate
Quality assurance
Produce
Deliver final production
Proven AI Review Methodology. Measurable Outcomes.
AI Review is only valuable when it produces defensible results, measurable efficiency gains, and repeatable workflows. CDS has deployed aiR across more than 80 projects for 29 billing clients, processing over 1.5 million documents through a structured implementation methodology that dramatically reduces client effort while delivering meaningful cost savings and review reduction.
Real Results Across Real Matters
| Case Study | Document Volume | Reduction | Cost Savings | Key Outcome |
|---|---|---|---|---|
| Case F Chat Review |
28,000 Messages | 80% | $28,000 | Reduced manual review to 4,000 documents |
| Case G Privilege Review |
15,000 Documents | 80% | $20,000 | 100% coverage and 375 review hours saved |
| Case H DOJ Trial Matter |
90,000 of 250,000 Documents | N/A | $115,000 | 2-week turnaround under trial pressure |
A Structured Framework for Defensible AI Deployment
CDS developed RAPID to ensure AI Review deployments remain transparent, repeatable, and defensible. Each phase establishes documented decision-making, attorney oversight, and validation protocols that support consistency across matters.
Understanding Technical Limits Before They Become Project Risks
Successful AI Review programs require awareness of platform limitations and workflow constraints. CDS designs implementations around known aiR boundaries while incorporating traditional review workflows where appropriate.
Continuous Learning. Defensible Outcomes.
Active Learning (TAR 2.0) combines experienced reviewers with machine learning to continuously prioritize the documents most likely to matter. CDS implements disciplined Active Learning workflows across Relativity, DISCO, and Everlaw using structured training protocols, validation testing, and defensible stopping criteria that reduce review costs without sacrificing quality.
Platform Expertise
Disciplined Active Learning Workflow
Seed Set
Select representative documents across custodians and issues.
Train
Reviewer decisions continually improve model accuracy.
Prioritize
Relevant documents surface first while lower-value material moves later.
Validate
Control sets, recall testing and elusion testing verify defensibility.
Training Doesn't End With the Algorithm
Successful Active Learning depends on disciplined human oversight. CDS establishes reviewer protocols, performs second-level QC on training documents, monitors reviewer consistency, and validates recall before concluding review.