# Case Data Router

*/Opportunities/Case_Data_Router*

## Opportunity Overview

**Wedge**: The initial beachhead targets medical records extraction for motor vehicle accident claims at personal injury firms. This niche experiences the most acute pain from high-volume, standard-format PDFs that overwhelm paralegals during initial case evaluation. Once the agent reliably routes vehicle accident intake data, the product expands horizontally into premises liability and workers compensation, then vertically into drafting initial demand letters based on the routed data.
**Timing**: Native multimodal LLMs with large context windows process massive, messy PDF bundles and images in seconds without brittle OCR pipelines. This makes zero-shot classification and extraction of unstructured legal documents highly reliable today, whereas two years ago it required costly, custom-trained ML models.
**Why This I C P**: Plaintiff personal injury firms operate on contingency and face massive inbound lead volume with low qualification rates. They are highly incentivized to automate intake and document routing to reduce upfront paralegal costs before a case generates revenue.
**Size Of Prize**: There are roughly 50,000 mid-sized plaintiff and personal injury law firms in the US. At an average annual replacement spend of $15,000 per firm on intake and document triage labor, the addressable prize is approximately $750M.
**Gap Narrative**: Mid-sized litigation firms receive hundreds of unstructured documents daily—medical records, police reports, client emails—that paralegals manually read, classify, and route to specific fields in practice management systems. Current intake software requires structured forms or relies on basic OCR that fails to extract relational context. The Case Data Router reads raw inbound files, categorizes the case type, and pushes extracted entities directly into the correct database schema.
**Defensibility**: The primary moat is workflow lock-in and deep integration into legacy practice management systems. As the router maps a firm's specific custom fields and internal routing logic, the switching cost becomes prohibitively high. The core extraction technology relies on foundational models, meaning the data moat is minimal and defensibility rests entirely on maintaining the deepest, most frictionless integration pipes.
**Why This Thesis**: An agentic workflow fits perfectly because document intake is an asynchronous, rules-heavy process that mimics a human reading a file and making a routing decision. Rather than asking lawyers to learn new software, the agent operates in the background, consuming emails and outputting structured database rows into existing systems.

## Opportunity Linked Thesis

**Thesis**: [Software](/Theses/Software)

## Opportunity Linked I C P

**Icp**: [Litigation Law Firm](/CompanyTypes/Litigation_Law_Firm)

## Opportunity Market Sizing

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**S A M**: ~$150M-$250M US mid-market and boutique litigation segment
**S O M**: ~$10M-$25M
**T A M**: ~45,000 US litigation firms × ~$12,000-$18,000/yr ≈ ~$540M-$810M
**Growth Rate**: ~12-16%/yr, driven by expanding eDiscovery file volumes and increasing fragmentation of state and federal electronic filing portals
**Paid Comparable Spend**: ~$40,000-$80,000/yr per firm in paralegal and clerk labor dedicated to manual document triage, renaming, and docket routing

## Opportunity Incumbents

- [ServiceNow Integration Hub](/Products/ServiceNow_Integration_Hub) — Tool
- [MuleSoft Anypoint Platform](/Products/MuleSoft_Anypoint_Platform) — Tool
- [In-House Python Scripts](/Products/In-House_Python_Scripts) — DIY
- [Shared Excel Trackers](/Products/Shared_Excel_Trackers) — Spreadsheet
- [Zapier Enterprise Teams](/Products/Zapier_Enterprise_Teams) — Tool
- [Manual Copy Paste](/Products/Manual_Copy_Paste) — DIY

## Opportunity Win Conditions

**Kill Thresholds**:
- Human-in-the-loop escalation rate exceeds 25% by day 14
- Conversion rate from trial to paid contract is below 20%
- Average time saved per paralegal is under 5 hours per week
- Customer acquisition cost exceeds $4,000 per mid-market firm
**Leading Metrics**:
- Document auto-routing success rate
- Time from court portal receipt to internal system filing
- Percentage of human-in-the-loop escalations per docket
- Daily active usage by paralegals during trial
- Integration onboarding hours required per firm
**What Proves Right**: Litigation firms route at least 80% of daily incoming court documents through the system without manual intervention within the first 30 days. Law firms authorize $1,000 to $1,500 monthly contracts immediately following a two-week trial period. Paralegal cohorts demonstrate 90% weekly retention and abandon their legacy shared Excel trackers for docket routing.
**What Proves Wrong**: Paralegals revert to manual downloading and renaming because the router fails to consistently extract metadata from non-standard county court dockets. Managing partners refuse the annual price point because they view manual triage as a sunk cost absorbed by existing salaried clerks. The system triggers excessive human-in-the-loop escalations that make automated routing slower than manual copy-paste.

## Opportunity Build Profile

**Hardest Part**: Achieving >95% extraction accuracy across highly variable, unstructured intake payloads—including nested email threads and poorly scanned PDFs—and mapping them cleanly to rigid destination schemas without forcing human triage.
**Min Viable Scope**: Focus exclusively on processing email-based personal injury intakes and routing them directly into one specific case management system. Deliberately leave out SMS ingestion, medical record summarization, and support for multiple practice areas.
**Cold Start Problem**: The system lacks the diverse baseline of messy, real-world intake documents required to build robust extraction prompts and guardrails. Break this by partnering with one high-volume firm to ingest 12 months of historical intake inboxes and manually grade the extraction accuracy.
**Time To First Value**: 2-3 weeks of onboarding to map destination schemas and run in shadow mode before fully automating the flow
**Data Moat Available**: true
**Technical Difficulty**: Moderate

## Neighborhood

### Where the gap lives

- [State and local government agencies](/Employers/State_and_local_government_agencies) — latent gap · Employers

### Applies thesis

- [Litigation Law Firm](/CompanyTypes/Litigation_Law_Firm) — applies thesis · CompanyTypes

### Incumbent in

- [In-House Python Scripts](/Products/In-House_Python_Scripts) — incumbent in · Products
- [Manual Copy Paste](/Products/Manual_Copy_Paste) — incumbent in · Products
- [MuleSoft Anypoint Platform](/Products/MuleSoft_Anypoint_Platform) — incumbent in · Products
- [ServiceNow Integration Hub](/Products/ServiceNow_Integration_Hub) — incumbent in · Products
- [Shared Excel Trackers](/Products/Shared_Excel_Trackers) — incumbent in · Products
- [Zapier Enterprise Teams](/Products/Zapier_Enterprise_Teams) — incumbent in · Products

### Embodies

- [Software](/Theses/Software) — embodies · Theses

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