Mining the carrier’s public litigation record.

A single denial looks like a judgment call; the same denial run a hundred times looks like a practice. JustineAI™ is being built to mine a carrier’s public footprint — prior published opinions, dockets, market-conduct examinations, regulatory consent orders — and surface the recurring playbook behind an individual file. A pattern facet will assemble, from public sources only, the carrier’s repeat denial rationales, its retained IME physicians, and the conduct regulators have already sanctioned, giving the attorney an evidentiary frame for institutional bad faith.

What IB is designed to do.

1. 01

   A pattern facet is being designed to read across a carrier’s public litigation history — published opinions and dockets surfaced through CourtListener-grounded retrieval — and cluster the denial rationales that recur file after file.

2. 02

   Market-conduct examination reports and regulatory consent orders, all public record, will be mined for prior findings on the same practices, giving the attorney sourced institutional context rather than an anecdote.

3. 03

   Retained-expert patterns are designed to surface: the same IME physician appearing across the carrier defense files, with the public matters and the opinions rendered laid out for the attorney to assess.

4. 04

   Every assembled pattern will be public-source only and citation-anchored — no proprietary data, no scraped private files — so the work product rests on records any court can take notice of.

5. 05

   The facet proposes the pattern; the attorney decides whether it rises to a practice, attests to the supporting record, and owns how it is pleaded — the platform never characterizes a named insurer on its own.

The AI reasons; the attorney decides.