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Scenario Analytics

Actuarial-grade risk modeling. For AI.

Monte Carlo simulation, loss triangles, Markov chains, survival analysis, and stress testing — the same quantitative tools insurers and risk managers use, purpose-built for AI risk.

The Suite

Every model a risk team needs.

Monte Carlo Simulation

Run 10,000 probabilistic scenarios across your defined time horizon. Get Expected Annual Loss, VaR at 95% and 99%, CVaR, and breach probability — real actuarial outputs, not estimates.

Monte Carlo Simulation — 10,000 Scenarios

Expected Annual Loss

$0

VaR (95%)

$0

CVaR (Tail Risk)

$0

Breach Probability

0.0%

Loss Distribution by Percentile

$0

P10

$0

P25

$0

P50

$0

P75

$0

P90

$0

P95

$0

P99

Mean

VaR 95%

Tail Risk

Scenario Factory

Describe a risk in plain language. The platform generates dozens of synthetic test scenarios, streams them in for review, and adds approved ones to your governance test suite.

Scenario Factory

Risk Description

AI must never offer refunds greater than $50 without manager approval

Markov Risk States

Model your AI fleet as a Markov chain transitioning between Low, Moderate, High, and Critical risk states. See steady-state probabilities and forward projections.

Markov Risk State Model

15%35%14%28%20%25%SAFEELEVATEDHIGHCRITICAL

30-Day State History

Actuarial Loss Triangle

Standard actuarial loss development modeling adapted for AI incidents. Project ultimate losses from reported loss history with IBNR reserves.

Loss Development Triangle

0mo

3mo

6mo

9mo

12mo

Q1 2025

$45k

$52k

$54k

$55k

$56k

Q2 2025

$38k

$44k

$47k

$49k

Q3 2025

$42k

$49k

$52k

Q4 2025

$35k

$41k

Q1 2026

$28k

Survival Analysis

Kaplan-Meier curves and hazard function estimates for governance failures. Compare survival profiles across governors and policy configurations.

Governor Survival Analysis

PII Shield

Financial Guard

Content Safety

25%50%75%100%0mo3mo6mo9mo12mo

Time between governance failures (months) — higher is better

Stress Testing

Define extreme scenarios — major provider outage, mass PII incident, regulatory enforcement — and model the financial impact. Compare across multiple stress cases.

Stress Testing — Scenario Comparison

extreme

P=2.1%

Major Provider Outage

Primary AI provider offline for 72+ hours

Revenue Impact

$2.4M

Agents Affected

89%

Recovery Time

72hr

severe

P=0.8%

Mass PII Incident

Simultaneous PII exposure across 5+ agents

Regulatory Fines

$1.2M

Records Exposed

45k

Legal Costs

$600k

moderate

P=4.3%

Coordinated Prompt Attack

Adversarial campaign exploiting agent chain

Financial Loss

$890k

Agents Compromised

3

Containment

4hr

Also Included

The full quantitative toolkit

Poisson Forecast

Expected incident frequency by time period with confidence intervals. Inform capacity planning and insurance reserve calculations.

Behavioral Clusters

Cluster analysis of agent behavioral patterns. Identify risk-similar groups and surface outliers that warrant investigation.

SPC Dashboards

Statistical process control charts for governance metrics. Detect when processes go out of control with Shewhart, CUSUM, and EWMA charts.

ROI Attribution

Break down total liability shielded into contributing components. See which governors, policies, and violation types drive financial return.

Model the risk before it models you.

Start free with 1,000 governance interactions. No credit card needed.