Turn your use case into quantum or hybrid code in minutes, execute on simulators or QPUs with full cost, speed and accuracy metrics.
From quantum specialists to classical developers exploring quantum advantage, Superpositions Studio serves the entire quantum computing ecosystem.
Quantum
Developers
Quantum software engineers and developers building the next generation of quantum applications.
AI/ML
Practitioners
Classical data scientists and ML practitioners exploring quantum advantages for optimization and machine learning.
Enterprise
R&D
Technical professionals in innovation and transformation units exploring quantum computing and competitive advantage.
Academic
Researchers
Physics, computer science, and engineering researchers advancing quantum computing theory and applications.
From quantum prototype to practical solution in five simple steps.
Describe Your Problem
I need to detect rare fraudulent card transactions in a stream of 20M payments a day using my rules and a trained risk score.
Or choose a template:
Oracle-based rare-event search. Build a reversible oracle that flags a transaction as fraud/not-fraud from rules or a scorer, then search for marked items using amplitude amplification.
Grover Search (ML oracle)
Dataset Requirements
Required datasets will appear here...
Recommended
Best for your use caseQSVM (Quantum Support Vector Machine)
Uses quantum kernels for classification. Reaches feature spaces hard to simulate classically; gains depend on the data and the chosen embedding.
Alternative Algorithms
Classical Baseline
Classical SVM (RBF kernel)
Standard support vector machine for comparison~8 minutes
88%
Why QSVM?
Auto-Generated Quantum Circuit
import pennylane as qml
from pennylane import numpy as np
dev = qml.device("default.qubit", wires=4)
@qml.qnode(dev)
def qnn(x, w):
qml.AngleEmbedding(
x,
wires=range(4),
rotation="Y",
)
qml.layers.StronglyEntanglingLayers(w, wires=range(4))
return qml.expval(qml.PauliZ(0))
w = qml.init.strong_ent_layers_normal(1, 4, seed=1)
print(qnn(np.ones(4), w))Code Features
Available Backends
Prediction Visualization
Architecture & Model Details
8
3
114
42s
Business Impact
Measurable value delivered by the model$127,500
234%
94%
67%
Performance Comparison
Classical
Quantum
Quantum Advantage
Future Projections
Next 12 months
With error rates improving by 10x, expect 3x additional speedup2-3 years
Fault-tolerant systems could achieve 100x speedup for large portfoliosScaling Analysis
Tclassical = O(n3)
Tquantum = O(n2)
Simple credit-based model. You only pay for what you actually use. No lock-in, unused credits roll over.
Pro
€20
/ per monthQuantum hardware access
Hybrid compute (CPU/GPU/QPU)
Dashboards & live monitoring
Export as Python
Scientific-paper reports
Price lock
Everything you need to transform industrial problems into quantum solutions.
AI Multi-Agent Navigator
Conversational workflow that maps your business problem to the right quantum algorithm, reshapes data if needed, selects hyperparameters, and explains choices in plain English.
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Start with a real use case. In minutes, Superpositions Studio delivers runnable quantum code, one-click runs on simulators or QPUs, full cost/speed/accuracy metrics, and a shareable PDF report.
Practical quantum algorithms — built for results, not hype.

The next breakthrough is waiting in superposition — let's collapse it together into reality.
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