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Use Case

AI-Powered Litigation Document Review

Process millions of pages of discovery in hours, not months. DiscoverLex combines semantic AI search, relationship mapping, and contradiction detection to give litigation teams cited answers from massive document sets — with full audit trails.

10M+

Page Capacity

< 4hrs

To First Insight

2-Pass

AI Verification

40+

File Formats

The Challenge

Why Is Traditional Document Review Failing?

Modern litigation routinely generates document sets measured in the millions of pages. A single commercial dispute can produce 2 to 5 million pages of discovery material spanning emails, contracts, financial records, internal memoranda, and digital communications. Traditional document review relies on teams of contract attorneys performing linear, keyword-based searches across these massive collections. The result is a process that takes 6 to 8 weeks, costs upward of $60,000 per month in reviewer time alone, and still misses critical evidence because keyword search cannot understand context, intent, or the relationships between documents.

6-8 weeks

Average manual review timeline for a mid-size case

$60K+/mo

Typical cost of contract reviewer staffing per matter

2-5M pages

Common discovery volume in commercial litigation

Pain Points Legal Teams Face Daily

  • !Keyword search misses documents that use different terminology for the same concepts
  • !Relationships between entities, dates, and events stay hidden across thousands of files
  • !Contradictions between witness statements and contemporaneous documents go undetected
  • !Inconsistent reviewer categorization leads to privilege review failures
  • !Linear scaling means doubling the documents doubles the cost and timeline
  • !Critical deadlines slip because review cannot keep pace with production volume

The Solution

How Does AI Transform Litigation Document Review?

DiscoverLex replaces the linear, keyword-dependent review process with an AI-powered pipeline that processes, indexes, and analyzes your entire discovery set in a fraction of the time.

  1. 1

    Ingest Your Entire Discovery Set

    Upload documents in any of 40+ supported formats — PDF, DOCX, TIFF, scanned images, email archives, and more. Our production-grade multi-engine OCR pipeline reliably processes typed text, handwritten notes, faxes, and degraded scans that defeat single-engine tools. Parallel processing handles millions of pages with consistent throughput, extracting metadata including dates, parties, and document types automatically.

  2. 2

    AI Indexes and Maps Relationships

    Once ingested, AI builds a semantic index of your document set and maps relationships between people, organizations, dates, monetary values, and events across every document. Entity extraction identifies connections that keyword search would never surface — like finding every document where a specific executive discussed a particular transaction, even when the transaction is referred to by different names.

  3. 3

    Search in Plain English

    Your team asks questions in natural language. Instead of constructing Boolean keyword queries, attorneys type questions like "What did the CFO know about the revenue recognition change before Q3?" Semantic search understands legal concepts, context, and intent — returning relevant passages from across the entire document set, ranked by confidence and relevance.

  4. 4

    Get Cited Answers with Contradiction Flags

    Every answer comes with full citation trails linking back to specific documents and page numbers. The AI cross-references facts across your corpus and automatically flags contradictions between documents — such as deposition testimony that conflicts with contemporaneous emails. Deep-dive analysis synthesizes evidence from multiple sources into comprehensive, verifiable answers.

Want to see all five core platform capabilities? Explore the full feature set.

Key Benefits

Why Litigation Teams Choose DiscoverLex

Hours, Not Weeks

Process millions of pages and run your first AI-powered searches within 4 hours of beginning ingestion. No more 6-8 week review timelines holding up case strategy.

Every Answer Cited

Every result links to source documents and page numbers. Full citation trails mean every finding is defensible, verifiable, and ready for court.

10-20x ROI vs Manual

Replace hundreds of hours of contract reviewer time each month. Enterprise clients typically see 10 to 20 times return on investment compared to traditional staffing models.

Enterprise Security

Built to SOC 2 Type II standards. End-to-end encryption. Tenant isolation. On-premise deployment available. Your documents never leave your secure environment.

Real-World Impact

What Results Can Litigation Teams Expect?

Here is how AI-powered document review compares to the traditional manual process for a typical mid-size commercial litigation matter.

Before: Manual Review

Traditional document review process

  • 6-8 weeks for initial review cycle
  • Keyword search returns thousands of false positives
  • Reviewer inconsistency causes privilege clawback risk
  • Relationships between entities found by chance, if at all
  • Contradictions across documents go undetected
  • $60,000+ per month in contract reviewer staffing

After: DiscoverLex AI Review

AI-powered litigation document intelligence

  • First AI-powered searches within 4 hours of ingestion
  • Semantic search understands legal concepts and context
  • Consistent AI categorization eliminates reviewer variance
  • Automatic relationship mapping across the entire corpus
  • Contradiction detection flags conflicting statements
  • 200+ hours of reviewer time saved per month, per matter

Litigation teams using DiscoverLex report saving 200+ hours per month of manual review time while achieving 2-pass AI verification and full citation coverage across every AI-generated answer.

Get Started

See AI Document Review in Action

Schedule a live demo with your own documents or explore our pricing to find the right plan for your litigation practice.

Need to understand pricing first? View pricing plans.