Quantum-inspired optimization —
built for real problems, not idealized ones.
Quicopt solves highly complex optimization problems with quantum-inspired algorithms — on standard hardware. No million-euro quantum computer. No “unsolvable”.
import numpy as np
from ortools.math_opt.python import mathopt
from quicopt import solve
# N binary variables, QUBO matrix Q — given
model = mathopt.Model()
x = np.array([model.add_binary_variable() for _ in range(N)])
model.minimize(x @ Q @ x)
result = solve(model) # one call — no signup, no API key
result["objective"] # minimized xᵀQxWhere established solvers hit a structural wall.
LPs, MILPs, and convex QPs scale to millions of variables. The wall isn’t size — it’s structure. When the Hessian is implicit, the objective is higher-order non-convex, or the cost comes from a simulator, exact methods stall, approximate, or don’t apply at all.
Implicit or dense Hessians
Smooth NLPs where Newton-class solvers stall — because the KKT system is too dense to factor, fills in catastrophically, or is only reachable through a simulator or learned model. Quicopt is purely first-order: gradients only, no Hessian, no factorization.
Higher-order, non-convex objectives
Degree-3+ polynomials and non-smooth logic don’t fit MILP/MIQP solvers natively. They require either massive auxiliary-variable reformulations or piecewise approximations that quietly change the problem. Quicopt solves the original objective directly.
Black-box objectives
When cost comes from a simulator, digital twin, or ERP model — not a formula — gradients and branch-and-bound proofs don’t apply at all. Quicopt works from input–output evaluations.
Quantum computers: €10–20 million
Real QPUs aren’t production-ready and cost tens of millions. Quicopt delivers quantum-inspired performance on standard hardware — today.
Your problem. Our solver. Your result.
How Quicopt works
Problem modeling
Your optimization problem is translated into quantum-ready form. Our team handles the modeling.
Quantum-Inspired Solving
Our algorithms run on standard hardware. No quantum computer needed — full performance today.
Integration & Output
Results via REST API, CSV or directly into your ERP. No black box — full traceability.
Quantum-Ready
Our modeling framework is hardware-agnostic. Migration to QPUs without reformulation.
Where others give up, Quicopt starts.
“We had implemented our procurement optimization with CP-SAT, but the runtime wasn’t acceptable under our hardware constraints. Quicopt gave us results up to 50× faster — and integrated directly into our workflow.”
Where Quicopt earns its place.
Four application areas where the structural advantages above translate directly into faster, sharper solutions.
Electronics & EMS
Multi-supplier BOM with thousands of parts and volume-tier pricing. Quicopt's domain-specific presolve exploits the natural structure of sourcing problems — BOM hierarchy, demand independence, supplier overlap — to shrink the search space dramatically before solving. On our active pilot: 10–50× faster than CP-SAT.
Power systems
AC optimal power flow is non-convex by physics — sinusoidal power-flow equations break QP relaxations. Grid topology optimization adds binary switch decisions, making the problem MINLP even in the DC linearization. Quicopt handles both natively, with no convex relaxation.
Process & metals
Blending, pooling, and recipe optimization with bilinear or higher-order terms — concentration × flow, yield × throughput, alloy composition. Exact global solvers (BARON, SCIP, Couenne) prove optimality on small instances but scale poorly; Quicopt delivers high-quality primal solutions on full-plant models in seconds.
QUBO, PUBO & HUBO
The native input format of quantum and quantum-inspired solvers. Quicopt solves binary problems of arbitrary polynomial degree directly — no reduction of higher-order terms to quadratic, no auxiliary-variable blow-up that today's QPUs require. Competitive with current quantum hardware at the problem sizes that actually matter — and it runs on a laptop.
Quicopt Compared
Real benchmark results against established solvers and quantum hardware.
| Compared to | Problem type | Quicopt advantage | Key insight |
|---|---|---|---|
| Gurobi | QCQP | Up to 100× faster, better solutions | No reformulation needed — Quicopt solves LABS natively |
| CP-SAT (OR-Tools) | Real-world MILP | Up to 50× faster | Active pilot with European electronics scale-up |
| Simulated Bifurcation | QUBO | Up to 10× lower avoidable cost | Better solution quality, not just speed |
| D-Wave (QPU) | QUBO | Comparable results | No qubit count or graph connectivity limits |
* Results from internal benchmarks. Performance varies by problem instance and size. The Gurobi comparison was performed on LABS instances from the QOBLIB dataset. We always recommend a direct test with your data. (QOBLIB)
Quantum performance. Without the quantum price.
Real quantum computers are fascinating — but €10–20M, not production-ready, and not yet scalable for your problems. Quicopt delivers today.
- ✓Standard hardware — PC, server or cloud. No special infrastructure.
- ✓Production-ready — Pilot running. Measurable results, real integration.
- ✓Scalable today — Thousands of variables, real constraints, productive use.
- ✓SaaS pricing — Monthly subscription, no CapEx, cancel anytime.
- ✓Quantum-Ready — Quantum-inspired framework migrates directly to QPUs when production-ready.
- ✗€10–20 million — Hardware investment before a single line of code runs.
- ✗Still experimental — Current QPUs are too error-prone for production.
- ✗Qubit limitation — Industrial problems far exceed today’s qubit count.
- ✗Cryo infrastructure — Operation near absolute zero — complex and expensive.
- ✗No SaaS — High integration and operational effort for every application.
Scientific foundation. Commercial execution.
- 1Quantum-inspired algorithms Hyper-efficient heuristics on classical hardware — no QPU required.
- 2Quantum-inspired framework Hardware-agnostic. Runs on CPU/GPU today, QPU tomorrow — no reformulation needed.
- 3Strength at high complexity Scales with thousands of variables where established solvers need multi-hour runtimes.
- 4Research base PGI-12 / FZJ Developed at the Institute for Quantum Computing Analytics (PGI-12), Forschungszentrum Jülich.
- 5Peer-reviewed Methodology published in PRX Quantum, Physical Review A and further refereed journals.
Our Origin
Built on decades of research excellence in mathematical optimization.
Quicopt is a spin-off from Forschungszentrum Jülich, one of Europe’s largest interdisciplinary research centers. Backed by Helmholtz Enterprise, we translate cutting-edge research into industrial-grade optimization solutions.
Our team combines deep expertise in quantum computing, mathematical optimization, and high-performance computing. We deliver algorithms that are not just theoretically sound, but proven in real-world applications.
Backed by
See Quicopt on your own problem.
No generic scenario — we compute with your real data.
Request Live Demo
Whether you have a specific optimization problem or want to explore what’s possible — reach out.