Underwrite cases with
conviction, not guesswork

We analyze historical verdicts with similar demographics, case types, and judges. We model how jury composition (age, income, education, prior trial experience) interacts with case facts to predict verdict probability and damage ranges. This is causal modeling, not statistical correlation—we understand the mechanisms driving jury decisions.

Yes. We map appellate panels, their reversal rates by issue type, and harmless error doctrine application. We model which elements of your trial are vulnerable to appeal reversal, and simulate appellate panel composition to quantify reversal risk.

We model settlement dynamics through case lifecycle: pre-discovery, mid-discovery, pre-trial, and post-trial phases. We simulate how trial risk, discovery burden, and cost escalation drive settlement offers—and predict when defendants will be forced to settle to avoid trial risk.

We have specialized models for personal injury, commercial litigation, IP/patent, employment, antitrust, and securities cases. Each has distinct jury behavior patterns, judge tendencies, and appellate dynamics. We can model your specific case type.

Yes. We identify correlation risk across your portfolio: shared judges, defendants, appeal jurisdictions, and case types. We highlight concentration risk and suggest case selection to improve diversification and portfolio return.

Traditional valuation relies on counsel estimates (often inflated for funding purposes). SimOracle is ground-truth calibration: we use historical verdicts, judge rulings, and appellate outcomes to build causal models of what actually drives case outcomes—independent of counsel bias.