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Pfs Analyzer

Reconcile PI Fact Sheets in Minutes, Not Hours

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 systematically validates draft builder discovery responses against source documents, producing a comprehensive issues memo with variance flags and full source traceability — turning hours of manual cross-referencing into a streamlined, auditable workflow.

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 dozens of pages — and a single missed provider or conflicting date can lead to supplemental disclosures, sanctions motions, or weakened case positions.

CaseMark's PFS Analyzer ingests your plaintiff fact sheets, supporting medical and financial documents, and draft builder responses, then automatically extracts, structures, and reconciles every data point. The result is a builder-ready output package and a lawyer-facing issues memo that flags every variance, gap, and low-confidence extraction — so your team can focus on strategy instead of spreadsheets.

How it works

  1. 1. Upload your 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 ratings

  3. 3. The system reconciles extractions against builder responses, flagging every variance and gap

  4. 4. Review the issues memo and builder-ready output, then export in your preferred format (DOCX, PDF)

What you get

  • Medical Provider Extraction Table

  • Wage-Loss & Employment Summary

  • Insurance & Lien Entity Register

  • Builder Response Variance Report

  • Issues Memo with Confidence Flags

  • Source Traceability Index

What it handles

  • Extracts medical providers, employers, and insurance/lien entities with full source traceability

  • Reconciles extracted data against draft builder responses with variance flagging

  • Assigns confidence levels (High/Medium/Low) to every extracted data point

  • Generates a lawyer-facing issues memo highlighting discrepancies and missing information

  • Produces builder-ready output with Bates-referenced citations

  • Identifies partial or missing source documents and labels output accordingly

Required documents

  • Plaintiff Fact Sheet / Initial Disclosures

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

    .pdf, .docx

  • Draft Builder Discovery Responses

    Draft discovery responses to be validated against source documents

    .pdf, .docx

Supporting documents

  • Medical Provider List / Specials Spreadsheet

    Treatment chronology, specials spreadsheet, or HIPAA authorization list detailing medical providers

    .pdf, .docx, .xlsx, .csv

  • Wage Loss Documentation

    Employer verification letters, pay stubs, W-2s, or tax returns supporting wage-loss claims

    .pdf, .docx, .xlsx

  • Insurance & Lien Disclosures

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

    .pdf, .docx

  • Client Intake Notes

    Internal questionnaires or intake forms with details that may not appear in the formal PFS

    .pdf, .docx

Why teams use it

Eliminate hours of manual cross-referencing between plaintiff fact sheets, specials spreadsheets, and builder draft responses

Catch missing providers, conflicting treatment dates, and incomplete lien disclosures before responses are served

Maintain full source traceability with Bates references and verbatim citations for every extracted data point

Standardize your PI discovery workflow across cases, attorneys, and jurisdictions with consistent, auditable output

Questions

What types of documents does the PFS Analyzer accept?

CaseMark's PFS Analyzer accepts executed plaintiff fact sheets, FRCP 26(a)(1) initial disclosures, MDL CMO forms, specials spreadsheets, treatment chronologies, wage documentation (pay stubs, W-2s, tax returns), EOBs, lien letters, subrogation notices, and draft builder discovery responses. You can upload PDFs, Word documents, and common spreadsheet formats.

How does the reconciliation process work?

CaseMark extracts every medical provider, employer, and insurance/lien entity from your source documents, then systematically compares each data point against your draft builder responses. Every variance — missing providers, conflicting dates, incomplete addresses — is flagged in a dedicated variance report with exact source citations.

What if I'm missing some of the source documents?

CaseMark will still process whatever documents you provide, but will clearly label the output as 'Partial' and identify exactly which documents or data categories are absent. This ensures your team knows precisely what gaps remain before finalizing responses.

Does the PFS Analyzer work for both state and federal court cases?

Yes. CaseMark's PFS Analyzer supports both federal (FRCP 26(a)(1)) and state court discovery frameworks. You simply specify your forum and jurisdiction during setup, and the system adjusts its extraction and reconciliation logic accordingly.

How accurate is the AI extraction, and does it replace attorney review?

CaseMark assigns a confidence level (High, Medium, or Low) to every extracted data point based on the specificity and completeness of the source material. While the AI dramatically accelerates extraction and reconciliation, all output is designed for attorney review before service or filing.

Can this handle MDL or mass tort cases with large volumes of plaintiff data?

Absolutely. CaseMark's PFS Analyzer is built to handle the structured discovery forms common in MDL and mass tort litigation, including CMO-specific plaintiff fact sheets and large specials spreadsheets with dozens of providers per plaintiff.

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