Live engine preview • simulated data

Risk at the speed of
the transaction.

AXIOM is Ace Hacker's quantum-accelerated intelligence engine for banking and finance. It scores fraud in real time, optimizes portfolios with quantum solvers, and runs Monte Carlo risk at a scale classical infrastructure cannot reach, all from one platform your quants and your regulators can actually audit.

< 8 msdecision latency (p99)
312×portfolio solve speedup
99.2%fraud recall @ 0.1% FPR
axiom://engine/live-monitor STREAMING
Throughput Latency Risk index
Txns / sec
48,210 +2.1%
Flag rate
0.34%+0.02
Model drift
0.011stable
Engine at a glance
0%
Fraud recall at 0.1% false-positive rate
Sentinel / AML
0
Speedup on 800-asset portfolio solve
Optima / QAOA
0 ms
p99 end-to-end scoring latency
Real-time API
0B
Transactions scored in pilot to date
Production pilots
One engine, four instruments

Every hard problem in a bank’s risk stack, under one roof.

AXIOM is modular. Each instrument solves a distinct class of problem with the right tool, classical ML where it wins, quantum where it genuinely pulls ahead, and it exposes every decision through an auditable API.

Sentinel • Instrument 01

Fraud caught in the gap between swipe and settle.

Every transaction is scored against a graph of accounts, devices, and merchants and a sequence model of the account’s own history. Anomalies surface in single-digit milliseconds, with an explanation a fraud analyst and a regulator can both read.

  • 01
    Graph neural network coreMoney-laundering rings hide in relationships, not single rows. The GNN scores the neighborhood, not just the transaction.
  • 02
    Per-account sequence modelsA £40 coffee is normal for one account and a red flag for another. Every account carries its own learned baseline.
  • 03
    Explainable by constructionEach score ships with the top contributing factors and a counterfactual, so decisions survive an audit.
GraphSAGETemporal attentionSHAPKafka ingestFeature store
Live transaction feedscoring…
Scored / sec
0
Flagged
0
Avg score time
0 ms
Anomaly space (t-SNE projection)2,000 txns
amount × velocity × graph-risk
LegitimateFlagged anomalyManual review
Detection performancehold-out set
Fraud-risk heatmap • merchant category × hour of dayrisk index 0–100
Optima • Instrument 02

The allocation space is astronomical. We search it anyway.

Constrained portfolio optimization is combinatorial: cardinality limits, sector caps, and transaction costs turn it into a problem classical solvers approximate under time pressure. Optima maps it to a QAOA circuit and finds allocations on the efficient frontier that classical heuristics miss.

Efficient frontier • solving live10,000 portfolios
risk (σ) → return (μ)Sharpe —
Sampled portfoliosEfficient frontierQAOA optimum
  • 01
    QAOA on the constrained problemCardinality and sector constraints are encoded directly into the cost Hamiltonian, not bolted on afterward.
  • 02
    Hybrid classical warm-startA classical relaxation seeds the circuit parameters, so the quantum solver converges in fewer iterations.
  • 03
    Hardware-agnosticThe same circuit runs on gate-based simulators today and on IonQ, IBM, and Quantinuum backends as they mature.
QAOA (p=6)COBYLACVaR objectiveQiskit / PennyLane
QAOA cost convergenceexpectation ⟨C⟩ per iteration
Optimal allocation8 sleeves
Horizon • Instrument 03

Tail risk you can trust, with fewer samples.

Classical Monte Carlo needs four times the samples to halve the error. Quantum amplitude estimation changes that scaling, so Horizon reaches a target confidence on VaR and CVaR faster, and shows its work.

Quantum Monte Carlo convergenceVaR 99% estimate
samples → estimate ± CI
Quantum-amplifiedClassical MC
P&L distribution • 1-day horizon10k scenarios
VaR —
ReturnsVaR 99%CVaR
Cross-asset correlation matrixρ • live regime
Aegis • Instrument 04

Quantum-safe before it needs to be.

The encryption protecting today’s transactions is harvestable now and breakable later. Aegis inventories cryptographic exposure and drives a phased migration to NIST post-quantum standards, without downtime.

  • 01
    Cryptographic bill of materialsAutomated discovery of every RSA and ECC dependency across services, so nothing is missed.
  • 02
    Hybrid rolloutClassical and post-quantum key exchange run side by side during migration, so nothing breaks.
  • 03
    QKD-readyFor the highest-value links, the architecture drops in quantum key distribution where it is justified.
ML-KEM (Kyber)ML-DSA (Dilithium)Hybrid TLSHSM integration
Migration postureestate coverage
Benchmarks • honest numbers

Where quantum wins, and where it doesn’t.

We benchmark against the best classical baseline, not a strawman. On some problems the quantum advantage is dramatic; on others classical ML is still the right call, and AXIOM routes to it automatically. Here is the current picture.

Solve time vs classical baselinelower is better
Classical solverAXIOM hybrid
Capability profilevs incumbent stack
Architecture • how a decision is made

From raw event to audited decision, in one pipeline.

Every score AXIOM emits flows through the same four stages. Classical and quantum compute live in the same graph, and the whole path is logged for audit.

01 / INGEST Event stream Kafka • feature store graph enrichment 02 / AI · ML Neural scoring GNN • sequence explainability 03 / QUANTUM Solver core QAOA • QMC hybrid orchestration 04 / DECISION Auditable API score + reason codes immutable audit log
Now in private pilots

Bring us your hardest risk problem.

AXIOM is in private pilots with a small number of institutions. If you run risk, fraud, or quant at a bank and want a technical walkthrough with your own data, we should talk.

Request a technical briefing → Read the architecture paper
SOC 2 Type II in progress • on-prem & VPC deployment • model cards on request