← Connor O’DeaLegal
2026 · In build

Juricratic

Litigation strategy modeled as a game, not a guess.

PythonNeo4jLangGraphAnthropic
Private repository

Problem

Litigation strategy is mostly built on intuition and war stories. Attorneys make consequential calls about settlement and posture with no model of how the other parties will respond.

Approach

  1. 01

    Model the case as what it structurally is: a multi-party game with payoffs, incomplete information, and sequential moves.

  2. 02

    Compute equilibria over realistic settlement positions, and model co-defendant dynamics where cooperating and defecting have asymmetric costs.

  3. 03

    Ground the payoffs in real court data instead of assumed numbers, so the simulation reflects outcomes that have actually occurred.

What it taught me

The model is only as good as the payoff estimates, and those are where domain expertise is irreplaceable. The valuable output turned out to be sensitivity analysis — which assumptions actually change the recommendation.

Architecture

Simulation
Python, game-theoretic solver over party payoffs
Graph
Neo4j — parties, claims, precedent relationships
Orchestration
LangGraph for multi-step case analysis
Data
CourtListener, eyecite for citation extraction
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