Predict.law is a Seattle-area legal AI startup using machine learning to help personal injury attorneys predict case outcomes and negotiate more effectively. Platform analyzes historical case data and fact patterns to provide case valuation, what-if scenario modeling (jurisdiction, judge, injury severity), polished prediction reports, and automated demand letter generation matching firm tone and branding. Founded 2023 by Pat Wilburn (ex-Thomson Reuters CSO, ex-Microsoft GM). Graduated from Mudita Studios. ~2,258 LinkedIn followers. $545K funding. Initial focus on contingency-based civil cases where case selection directly impacts firm economics.
Company Info
- Founded: 2023
- Team size: 1-10 employees
- Funding: $545.4K
- HQ: Germany
- 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, Predict Law is used in these workflows:
What practitioners struggle with
Real frustrations from legal professionals — the problems Predict Law addresses (or should address). Sourced from practitioner reviews, Reddit threads, and case studies.
PI firm settles 200 cases a year but has no aggregate data on what case types settle for what amounts, which providers write the best medical narratives, or which adjusters are most likely to lowball — every case starts from zero institutional knowledge because the data is locked in individual attorney memories and closed file cabinets
Plaintiff lawyer is about to send a demand letter or walk into mediation with a case that could be worth far more than the insurer's first offer, but they're still guessing which facts, videos, and witness moments actually make jurors or mediators care — traditional focus groups take too long, cost too much, and one loud participant can distort the whole read on case value.
Where it fits in your workflow
Before Predict Law
PI attorney evaluates potential case during intake → needs to estimate case value and success probability before accepting on contingency → traditionally relies on gut experience and informal comparisons
After Predict Law
Case accepted → Predict.law generates valuation and comparable analysis → attorney uses data in demand letter and negotiation → settlement or trial decision informed by prediction
Integrations & hand-offs
Predict.law (valuation + prediction) → PI case management system (case data); → demand letter (auto-generated); → settlement negotiation (data-backed reports for adjuster/mediator)
Community Data
Loading practitioner-sourced data…