A working quantum PoC on your data in a defined scope.
Pick a vertical. We run your problem through the same simulation engine we built, using templates already profiled against IBM Eagle and IonQ Aria. You get working code, a benchmark, and a decision-ready report. Fixed scope, fixed price.
What's in the box
Every PoC-in-a-Box engagement delivers the same five artefacts. No open-ended scope.
1. Problem formulation
Your business problem translated into a quantum-ready objective with constraints, decision variables, and success metrics.
2. Working circuit
Executable code built on our pre-profiled ansatz templates. Runs on the DeployQuantum simulation engine.
3. Classical baseline
Head-to-head comparison against the classical solver your team would otherwise use. Same data, same constraints.
4. Hardware-ready export
Qiskit, PennyLane, and Qulacs exports. Profiled noise models for IBM Eagle and IonQ Aria so you can see what moving to real hardware would cost.
5. Decision report
A plain-English read of what worked, what did not, and whether it is worth committing to a production build. Not a research paper.
Fixed timeline
Kickoff to final report in a defined scope. Daily standup during execution. No retainer, no milestones that drift.
Four verticals, one engine
Each vertical has its own templates, encoders, and baseline classical solver. Pick the one that matches your problem.
Portfolio Optimization
Optimize a live portfolio against your own constraints: risk limits, sector caps, turnover budgets, ESG tilts.
- Templates
- Pre-built QAOA and amplitude estimation ansätze. Markowitz baseline included.
- Inputs
- Holdings, returns covariance, constraint matrix.
- Output
- Optimized allocation + quantum-vs-classical comparison + Qiskit/PennyLane export.
Logistics & Routing
Quantum-native solver for vehicle routing, scheduling, and network flow problems where classical heuristics hit their limit.
- Templates
- QAOA for VRP, job-shop, and min-cost-flow. Baseline against OR-Tools.
- Inputs
- Network graph, demand vector, vehicle and time constraints.
- Output
- Route/schedule plan + cost delta vs classical + deployable code artefact.
Drug & Materials Screening
Ground-state energy and binding-affinity estimates for small molecules or lattice systems with a specific chemistry question.
- Templates
- UCC-SD VQE ansätze for molecular Hamiltonians. Jordan-Wigner and Bravyi-Kitaev encoders.
- Inputs
- Target molecule or lattice, active space definition, basis set.
- Output
- Energy curves + convergence analysis + hardware-ready circuits.
Financial Risk Simulation
Quantum-accelerated Monte Carlo for derivative pricing, VaR, and exotic payoff simulation where classical sampling is the bottleneck.
- Templates
- Quantum amplitude estimation circuits for price and risk metrics.
- Inputs
- Payoff specification, underlying dynamics, confidence interval target.
- Output
- Estimated price / risk metric with convergence analysis + classical-sampler comparison.
Who it is for
- ,CTOs and heads of R&D who need to answer "does quantum actually move the number?" before committing to a roadmap.
- ,Teams evaluating a hardware vendor and want a vendor-neutral benchmark on their own problem first.
- ,Innovation leaders who have board pressure to "do something with quantum" and need a defensible data point.
Who it is not for
- ,Academic research teams doing novel algorithm development. We run templates, not experiments.
- ,Organizations without a defined problem. The first 30 minutes of the discovery call decides whether a PoC is the right next step or not.
- ,Teams wanting "quantum advantage theatre." We report the comparison honestly, including when classical wins.
The same engine we use on your PoC is the one we built.
Circuit Simulation, Optimizer, Ansatz, Noise, Analysis, Interface. Six specialized engines profiled against IBM Eagle and IonQ Aria. See the stack.
Bring us the problem. With a defined scope, you have the answer.
30-minute discovery call. Scoped proposal within 48 hours. Kickoff the week after.