🛡️ ARF – Prevent the Next AI Incident Simulated ✅ 54/54 tests passed
See all three ARF decisions: APPROVE, ESCALATE, and DENY.
📋 Choose a real‑world scenario
✈️ Air Canada – Chatbot hallucination
🌩️ Cloudflare – Configuration cascade (Feb 2026)
💀 PocketOS – Autonomous coding agent deletes production DB
Load Scenario & Evaluate Risk
📘 Understanding your results (click to expand)
Risk score (posterior mean) – probability a similar action would fail.
95% credible interval – where the true failure probability likely lies.
Prior mean – the model’s belief before seeing data.
Policy decision – APPROVE (<20%), ESCALATE (20‑80%), DENY (>80%).
Expected loss – risk × financial impact.
📊 Risk Scoring Result
⚡ Decision latency: <50ms
Risk score (posterior mean) ⓘ : 95% credible interval ⓘ : Prior mean: Policy decision ⓘ :
📋 Copy full report
📌 Deterministic Probability Thresholding: Approve if risk <0.2, Escalate if 0.2–0.8, Deny if >0.8.
👤 Escalate = human review required – you stay in control
🧠 Why did ARF decide this? (counterfactuals)
🔒 SOC2 Type II (Audit ready)
🛡️ ISO 27001 (Compliant)
📜 GDPR Ready
📉 Without ARF
🛡️ With ARF (governance)
🔍 Counterfactual analysis: What would have happened if the agent acted alone vs. with ARF governance.
📊 Compare all scenarios at a glance
Scenario Risk 95% CI Decision Expected Loss (Without ARF) Loss Avoided (With ARF)
All numbers illustrative. Real engine requires pilot access.
📋 Recent Incidents (Simulated)
Time Service Metric Value Risk Action
Data shown is simulated for demonstration purposes only.
✅ 54/54 pressure tests passed | 🧪 3 active pilots | 👥 Founder‑led