Public cloud — Quantum Computing
A managed quantum platform for the teams getting ready. Cloud-based emulators in Jupyter notebooks today. On-demand access to real Quantum Processing Units when your algorithm outgrows the simulator. One interface, multiple hardware technologies, no vendor lock-in.
Emulators and real QPUs through the same workspace.
Pulser, Perceval, Qiskit, and others — pick what fits your algorithm.
Simulate first, run on hardware when your circuit is ready.
Switch between quantum hardware technologies through the same interface.
Why explore quantum now
Quantum hardware is moving fast. The cost of starting is low. The cost of waiting until "it's mature" is being unfamiliar when it matters.
01
Some optimization, simulation, and search problems grow exponentially in classical complexity. Quantum algorithms offer polynomial or exponential speedups on a subset of these — useful when the problem actually fits.
02
Classical simulation of quantum systems leans on approximation. Direct quantum simulation can model molecular structures, energy levels, and probabilistic systems closer to reality — which matters when accuracy compounds downstream.
03
Quantum machines explore many states simultaneously via superposition. On problems that fit, this can mean faster convergence with less raw compute — relevant for sustainability targets and the workloads where classical compute is already expensive.
Two managed products
Most quantum work starts in simulation — develop the algorithm, debug the circuit, validate the approach. When the circuit is ready, the same code runs against a real QPU. One workflow, two destinations.
PRODUCT/01 · SIMULATE
CLOUD-BASED SIMULATION · NO HARDWARE REQUIRED
Run quantum circuits on classical simulators hosted on intSignal infrastructure. Pre-configured Jupyter notebooks with the SDK of your choice — Pulser, Perceval, Qiskit, and others. No environment setup. No GPU procurement. Just open the notebook and start.
PRODUCT/02 · RUN
REAL QUANTUM HARDWARE · MULTIPLE TECHNOLOGIES
When your circuit is ready, run it on actual quantum hardware. intSignal integrates with QPU partners across multiple physical paradigms — superconducting, trapped ion, neutral atom, photonic — under one unified API. Switch backends without rewriting your code.
Same notebook, both destinations
The point of a managed quantum platform isn't to abstract away the physics. It's to remove the operational friction. The circuit you debug against a simulator is the same circuit you send to a QPU — same notebook, same code, different target backend.
Switch between SDKs to use the abstraction that fits the algorithm. Pulser for neutral-atom programming. Perceval for photonic circuits. Qiskit for the broader ecosystem.
Multi-technology platform
No single quantum hardware approach has emerged as the standard. Different paradigms have different strengths — fidelity, connectivity, scalability, operating conditions. Through intSignal you can target any of them without rebuilding your stack.
CRYOGENIC · GATE-BASED
Qubits made from superconducting circuits at near-absolute-zero. Fast gates, established tooling. Used by major industry players.
IONS · HIGH FIDELITY
Individual ions held in electromagnetic traps and controlled with lasers. Long coherence times, high gate fidelities.
RYDBERG · ANALOG + DIGITAL
Neutral atoms arranged in optical tweezer arrays. Supports both analog Hamiltonian simulation and gate-based circuits.
PHOTONS · ROOM-TEMPERATURE
Information encoded in photons. Operates at room temperature, naturally suited for quantum networking and certain sampling problems.
Where quantum is being applied
Quantum is research today and selective production tomorrow. These are the domains where being familiar with the stack matters before the broader inflection.
CHEMISTRY · MATERIALS
Next-generation batteries, catalysts, renewable energy systems. Direct quantum simulation models molecular behavior more accurately than classical approximations.
PHARMA · LIFE SCIENCES
Molecular interaction modeling, protein structure analysis, biological mechanism simulation. Accelerating R&D cycles where computational cost is the bottleneck.
FINANCE
Quantum-enhanced Monte Carlo, portfolio optimization, and pattern detection. Complementing existing quantitative methods, not replacing them.
SECURITY · DEFENSE
Understanding what quantum hardware can break — and what algorithms remain secure. Critical for any organization with long-lived data classifications.
LOGISTICS · ENERGY
Vehicle routing, network flow, energy grid balancing. Problems where the solution space grows exponentially and quantum heuristics can offer practical advantage.
RESEARCH · ACADEMIA
Quantum machine learning, error correction research, hybrid classical-quantum algorithms. The applied research that builds the next decade of quantum software.
Honest framing
Quantum is not a replacement for classical compute. It's not faster at everything. It's not production-ready for most workloads. The current generation of QPUs is noisy, qubit counts are limited, and decoherence is real.
Quantum is a credible long-horizon capability with measurable advantage on specific problem shapes — molecular simulation, certain optimization formulations, sampling tasks. The teams that will benefit when the hardware matures are the ones learning the stack now, on managed platforms, without standing up their own.
Our role is to give you that learning surface — pay-as-you-go, no hardware procurement, no vendor lock-in, with the option to run real quantum jobs alongside the simulator when your algorithm is ready.
FAQ
If yours isn't here, ask in the consultation — we'd rather flag the awkward bits early than discover them in production.
The emulators run on intSignal infrastructure. The real Quantum Processing Units are accessed through partner integrations — superconducting, trapped ion, neutral atom, and photonic. You access them through the intSignal platform with one set of credentials and a unified API, but the physical hardware is operated by specialized quantum providers.
Qiskit, Pulser, Perceval, and others — the major SDKs in active use across the quantum community. The pre-configured notebooks come with these installed and authenticated against the platform. You can also bring your own environment if you prefer.
Pay-as-you-go. Emulators bill for the compute time of your notebook session. QPU jobs bill based on actual quantum processing time — generally measured in shots and circuit depth. Simulate aggressively on the emulator, then run on a QPU only when the circuit is validated.
The emulator runs full state-vector simulation up to 20 qubits, which is the practical limit for classical simulation of arbitrary quantum circuits. For larger systems, approximate methods (tensor networks, MPS) are supported, or you move to a real QPU.
Yes. Hybrid classical-quantum is the practical reality of quantum software today — variational algorithms (VQE, QAOA), quantum-enhanced ML, classical pre/post-processing around quantum subroutines. The notebook environment has access to standard classical libraries alongside the quantum SDKs.
The cryptographic implications of quantum computing are real, but the response isn't a quantum platform — it's classical algorithms designed to resist quantum attacks (NIST's PQC standards). The Security and Compliance areas of intSignal address that directly; quantum computing here is about exploring the compute paradigm itself.
For a specific subset of workloads — primarily research, algorithm development, and selected optimization or simulation problems — yes. For most production workloads, no. Today this is a learning and prototyping environment for teams positioning themselves for when the hardware matures further. We're honest about that, and we'll be honest with you about whether your specific use case fits.
Tell us about the problems you're hoping quantum can address. We'll be honest about what fits today, what's promising, and how to start without overcommitting.