AI-powered platform purpose-built for mass tort litigation, settlement analytics, and claims processing. Co-founded by Matt Francis (CEO), based in Charlotte, NC. Core capability: automated medical record review with claimed 98% accuracy and 10x speed improvement. Platform includes Pattern Case Score for litigation visibility, settlement-ready report export, and military records analysis. Beasley Allen (top US mass tort firm) is a confirmed customer — case study documents accelerated case workup for PFAS litigation with military records. Transactional pricing based on case volume (no published rates). Integrates with case management platforms via API (export to popular CMS, no specific platforms named). Active at MTMP (Mass Tort Made Perfect) conference. Competitors include Supio, Darrow, and general AI legal tools (Legartis, DeepJudge). No security certifications documented despite handling HIPAA-sensitive medical records — a significant gap. No Reddit presence. No G2/Capterra reviews found. Early-stage company with limited public profile outside mass tort conference circuit. Mass tort legal tech is a growing niche as firms seek to scale case processing without linear headcount growth.
Company Info
- Founded: 2020
- HQ: United States
- Sector: Litigation
What We Haven’t Verified
This page was assembled from publicly available information. Feature claims and workflow mappings are based on what the vendor and third-party listings publish — not hands-on testing or practitioner feedback.
Workflows
Based on practitioner evidence, Pattern Data is used in these workflows:
What practitioners struggle with
Real frustrations from legal professionals — the problems Pattern Data addresses (or should address). Sourced from practitioner reviews, Reddit threads, and case studies.
Medical records arrive as 500-2,000 page PDFs that a paralegal spends 8-20 hours manually reading and summarising into a chronology — the bottleneck that delays every PI demand
Plaintiff firm can't scale past 100-200 active cases because every additional case adds linear paralegal/attorney hours for med records, chronologies, and demand work — the economics break without automation
Board meeting prep is a quarterly fire drill — the corporate secretary scrambles to assemble board books from 6 different sources, track director consents across time zones, maintain minutes archives, and ensure governance resolutions are properly filed, all while the GC changes the agenda 48 hours before the meeting.
Mass tort firm managing 5,000 PFAS water contamination cases needs to identify which claimants have documented diagnoses matching the MDL's criteria — manually reviewing military and medical records for each one would take years and cost millions in contract attorney fees
Where it fits in your workflow
Before Pattern Data
Mass tort intake → medical records collected from clients → records uploaded to Pattern Data for AI analysis
After Pattern Data
Pattern Data analysis → Pattern Case Score → settlement-ready reports exported → case management system → settlement distribution
Integrations & hand-offs
Case management platforms (export via API — no specific CMS named)Settlement administrators (claims processing workflow)Court filing systems (MDL documentation)
Community Data
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