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Pfs Analyzer

Reconcile PI Fact Sheets & Builder Drafts in Minutes

12 minutes with CaseMark

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Best for a quick one-off job. Add your email, upload the files, and we'll run the workflow and send the result to your inbox.

1. Add your email so we know where to send the result.

2. Upload the files you want analyzed.

3. Run the workflow and we'll take it from there.

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Save and reopen matters, keep documents together, refine the output, rerun with changes, and export or share polished work product when you're done.

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Scroll for the workflow details below if you want to review what this run handles, what documents help, and what the output looks like.

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Workflow

Pfs Analyzer

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Workflow

Pfs Analyzer

Overview

CaseMark's PFS Analyzer automates the extraction and reconciliation of medical provider, wage-loss, and insurance/lien data from personal injury plaintiff fact sheets and initial disclosures. It cross-references all extracted data against draft builder discovery responses, producing a comprehensive variance report and issues memo with full source traceability and confidence scoring.

Reconciling plaintiff fact sheets against builder discovery responses is one of the most tedious and error-prone tasks in personal injury litigation. Paralegals and associates spend hours manually cross-referencing medical providers, wage records, and insurance disclosures across multiple documents, and a single missed variance can result in deficient responses or costly supplementation.

CaseMark's PFS Analyzer ingests all source documents, extracts every provider, employer, and lien entity with verbatim citations and confidence scores, and automatically reconciles the data against draft builder responses. The result is a builder-ready output package and a lawyer-facing issues memo that highlights exactly where attention is needed — reducing hours of manual work to minutes.

How it works

  1. 1. Upload plaintiff fact sheets, builder draft responses, and supporting medical, wage, and insurance documents

  2. 2. AI extracts and structures all provider, employer, and lien data with source citations and confidence scores

  3. 3. The system reconciles extracted data against builder drafts and flags every variance

  4. 4. Review the issues memo, export reconciliation tables and builder-ready output in DOCX or PDF

What you get

  • Medical Provider Extraction Table

  • Wage-Loss & Employment Summary

  • Insurance & Lien Entity Register

  • Builder Draft Variance Report

  • Issues Memo with Confidence Flags

  • Missing Document & Data Gap Inventory

What it handles

  • Structured extraction of medical providers, employers, and insurance/lien entities with source citations

  • Automated reconciliation against draft builder responses with variance flagging

  • Confidence-scored data points with verbatim source traceability

  • Wage-loss audit with employment gap and documentation analysis

  • Issues memo generation with actionable flags for attorney review

  • Support for federal FRCP 26(a)(1) and state court frameworks

Required documents

  • Plaintiff Fact Sheet / Initial Disclosures

    Executed plaintiff fact sheet, FRCP 26(a)(1) initial disclosure packet, or MDL CMO form

    .pdf, .docx

  • Draft Builder Responses

    Draft discovery responses to be validated against plaintiff source documents

    .pdf, .docx

Supporting documents

  • Medical Provider List

    Specials spreadsheet, treatment chronology, or HIPAA authorization list

    .pdf, .docx, .xlsx

  • Wage Loss Documentation

    Employer verification letters, pay stubs, W-2s, or tax returns

    .pdf, .docx, .xlsx

  • Insurance Disclosures

    EOBs, PIP/MedPay documentation, lien letters, subrogation notices, or Medicare/Medicaid status

    .pdf, .docx

  • Client Intake Notes

    Internal questionnaires with details that may have been omitted from the formal PFS

    .pdf, .docx

Why teams use it

Eliminate hours of manual cross-referencing between plaintiff fact sheets, medical records, and builder drafts

Catch omissions and discrepancies in builder responses before service with automated variance detection

Maintain full audit trails with source-cited, confidence-scored data points for every extracted fact

Accelerate MDL and mass tort workflows where dozens or hundreds of plaintiff fact sheets require consistent processing

Questions

What documents do I need to get started?

At minimum, you need the executed plaintiff fact sheet or FRCP 26(a)(1) disclosures and the draft builder responses. CaseMark will also process medical provider lists, wage documentation, and insurance disclosures for a complete reconciliation. If any documents are missing, the output is clearly labeled as partial.

How does CaseMark handle data traceability?

Every extracted data point includes the source document and page reference, the verbatim text from the source, and a confidence rating (High, Medium, or Low). CaseMark ensures nothing is presented without a traceable origin, so attorneys can verify every fact before filing.

Can this handle MDL plaintiff fact sheets?

Yes. CaseMark's PFS Analyzer supports MDL CMO forms, standard plaintiff fact sheets, and FRCP 26(a)(1) initial disclosure packets. The system adapts its extraction framework to match the specific form structure you upload.

What does the variance report show?

The variance report compares every data point extracted from the plaintiff's source documents against the corresponding entries in the draft builder responses. It flags omissions, discrepancies, and inconsistencies so your team can correct builder drafts before service.

Does this replace attorney review?

No. CaseMark accelerates the extraction and reconciliation process, but all output requires attorney review before service or filing. The issues memo and confidence scores are designed to focus attorney attention on the items that need human judgment.

How long does the analysis take?

Most PFS analyses complete in approximately 10-15 minutes depending on document volume and complexity. This replaces what typically takes paralegals and associates several hours of manual cross-referencing.

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