Pattern Data

Pattern Data: Litigation Case Management software

The operating system for mass tort litigation.

DL Score 73 · Leader
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Litigation Case ManagementLitigation AnalyticsCase Management

Pattern Data is a case management platform for mass tort litigation. ⁣‌‍​‌⁠⁠‌​⁠‍⁠​‍‌‍​⁣It organises every record in a docket against the criteria of each litigation, flags gaps and open issues, and shows reviewers where to act next. The product is built for plaintiff firms and claims administrators handling large multi-claimant matters across multiple MDLs, where case files change as requirements evolve.

Product

Pattern Data

Founded

2020

Headquarters

United States

Funding stage

Unfunded

Last updated

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Overview

What Pattern Data does

Pattern applies litigation-specific criteria across an entire docket in one system and measures each case against the rest of the inventory. ⁣‌‍​‌⁠⁠‌​⁠‍⁠​‍‌‍​⁣When criteria change during an MDL, the same logic is reapplied, so teams do not need to revisit every file. Each suggested finding links back to the page it came from, and a reviewer accepts, edits or rejects it. Gaps are graded Critical, Major or Minor, with an explanation of their effect on the claim. Review moves through the litigation's criteria one step at a time, and issues roll up across the inventory to show where work should be prioritised. Allocation criteria can be applied at scale, with results reported by tier. The workflow runs in three stages. Screen validates exposure and injury early to qualify cases faster. Develop analyses records, surfaces gaps and models valuation across the inventory. Settle applies eligibility and allocation logic before submission. The vendor says it is trusted by top mass tort firms nationwide, and its website lists the litigations it supports as AFFF/PFAS, Camp Lejeune, CPAP, Chlorpyrifos and Depo-Provera. Customer testimonials come from several plaintiff firms. The vendor also publishes research on model refinement and litigation analysis through Pattern Labs.

What it does

Pattern Data core capabilities

See where every case stands

Baseline gates, open issues and chronology on each case's first screen.

Check every finding against its source

Each suggested finding links to its source page for review.

Know what every case is missing

Gaps graded Critical, Major or Minor, with their effect on the claim.

Give reviewers a clear path

Review proceeds through litigation criteria one step at a time.

Point your team where the docket needs it

Issues roll up across the inventory to prioritise work.

Apply settlement logic at scale

Allocation criteria applied across inventory, reported by tier.

Technical specifications

  • AI-powered
  • Inventory-level litigation criteria
  • Extraction, classification, and scoring
  • Mass tort litigation support
  • Employee count: 45

Case studies

No case studies yet

Pattern Data doesn’t have a client-confirmed case study on DreamLegal yet. Try exploring different products for exploring case studies.

Trust & compliance

Pattern Data security at a glance

Security certifications

Not publicly listed on the product profile.

Named enterprise customers

Motley RiceBeasley AllenWagstaff & CartmellFranco LawOSC LawLevin Papantonio

Pricing details

Pattern Data pricing

No pricing info is available for this product right now. Please check other products or visit their website.

Product videos & screenshots

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Product interface

Pattern Data Interface

Comparisons

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Transparency

Pattern Data sources

Pages used to generate and verify this profile.

  1. 1https://patterndata.ai/

FAQs

Frequently asked questions about Pattern Data

Pattern Data is aimed at plaintiff firms and administrators managing high-stakes litigations across multiple MDLs. Pattern Data's website says it is trusted by top mass tort firms nationwide and names customers including Motley Rice, Beasley Allen and Wagstaff & Cartmell.

Every suggested finding links to the page of the record it came from. A reviewer then accepts, edits or rejects the finding, so the team keeps control of the final decision. The vendor describes this as AI proposing findings and the team making the call, with Pattern surfacing both the finding and the proof.

Pattern applies the criteria across the entire inventory in one system and reapplies that logic when requirements change. Teams do not need to go back into each file manually to keep pace. Reviewers move through the criteria one step at a time, which the vendor says helps new reviewers get up to speed quickly.

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