PROJECT AEGIS

Asynchronous Quantum-Classical Mesh · Credit Card Fraud Detection · Team Beerantum
RECORDED RUN
VQC + QAE · 4 qubits
Target: IonQ Forte via Braket
dataset: —
Transactions
0
Cleared synchronously
—
Sieve latency p50 / p99
—
Quantum queue
0
Frauds blocked
0
False declines
0

Mesh pipeline

Payment gateway feed
0
auth requests
→
Synchronous Sieve · XGBoost + SMOTE
0
approve / decline < 50 ms
⇢
Async Quantum Adjudicator · VQC + QAE
0
ambiguity band — · out-of-band verdict

Live authorization stream

TxnTimeAmountSieve P(fraud) LatencyStatusTruth
waiting for feed…

Quantum adjudications

no ambiguous transactions yet — the sieve is clearing traffic

Offline evaluation (held-out test set)

This is a recorded run, replayed in the browser. Every number shown — sieve probabilities, VQC and QAE scores, verdicts and Shapley attributions — was produced by the trained models on held-out transactions and written out ahead of time by scripts/export_static_demo.py; the page replays those records rather than scoring in real time, which is what lets it run on static hosting. The feed is also enriched to ~8% fraud and ~22% ambiguous cases for visibility, against a real prevalence of 0.172% fraud and 0.6% ambiguous, so the "cleared synchronously" figure here sits well below the 99.4% measured on the real distribution. To watch the models score live, run the FastAPI server from the repository.