Why hybrid?
Because no single engine wins everywhere. Routing and scheduling problems grow explosively with size and constraints — the right answer is choosing the right method per problem, automatically.
Model → Simulate → Solve → Act.
Your real constraints — setups, capacities, time windows, depots, crew, cargo — encoded into a solvable problem.
Candidate plans stress-tested against disruption, demand shifts, and constraint changes before anything ships.
The hybrid engine picks the method that wins on your problem and returns a high-quality answer fast.
Schedules, routes, and ETAs your team can execute — re-optimized live when reality changes.
Classical, quantum-inspired, and quantum — under one roof.
Every problem that enters Qavis is decomposed and matched to an engine. Proven classical solvers handle structure. ML models supply demand, ETA, and disruption forecasts. Quantum-inspired and quantum-hybrid methods take the large, tightly-constrained cores where they earn their place.
The switching is automatic. Your planners see one answer — the best available one.
Value today — no quantum hardware required.
Quantum-inspired algorithms run on CPU/GPU hardware you already have access to, and they scale to instances where classical heuristics start leaving value on the table. This is where most customers see their first step-change: 15–160× faster runs on large, tightly-constrained problems.
It's also the honest on-ramp: benchmarkable now, on your data, without waiting for hardware roadmaps.
Which job goes to which backend? Not your problem.
The routing layer profiles each sub-problem — size, constraint density, time budget — and dispatches it to the engine that wins on it. We benchmark continuously, so the dispatch decision is based on measured performance, not marketing.
We're QPU-agnostic by design: IBM, AWS Braket, Azure Quantum, D-Wave, IonQ, Quantinuum, Xanadu — plus quantum-inspired platforms.
Your SAP, ERP, and on-prem systems stay untouched.
Qavis sits beside your stack, not inside it. We read from and write to SAP, ERP, TMS, and WMS systems; deployment is cloud-native or on-prem to match your security posture; and models learn from your operational data for customer-specific accuracy.
No rip-and-replace. No migration project. No new tool for your planners to fight.
Honesty is the credibility asset.
Quantum-hybrid helps on large, tightly-constrained problems. On small instances, classical wins — and we'll tell you so.
We benchmark honestly, pick the engine that wins on your problem, and never sell a demo as an answer. Guided by research-grade quantum-optimization expertise spanning automotive supply-chain work.
Want the benchmarks, not the pitch?
Bring your hardest instance. We'll run it across engines and show you the numbers — including where classical wins.