Now piloting · Quantum-optimized routing

Quantum optimization for complex decisions.

QuGradient combines quantum-inspired methods, hybrid quantum-classical computing, and advanced optimization to solve high-value operational problems — across logistics.

Spun out of QuMatrix · backed by 350+ peer-reviewed papers and a decade of applied optimization.

RouteIQ · run #142
Routing cost vs current solver−6.2%
Stops planned3,418
Constraints honored100%
Illustrative — your numbers come from a benchmark on your data.
The science behind QuGradient — research & engagement network at QuMatrix IBM CERN Los Alamos National Laboratory Rigetti Strangeworks Barcelona Supercomputing Center Universitat de València Oceaneering Protiviti Uzara Wells Fargo

The opportunity

Operational complexity is outgrowing traditional logistics optimization.

Most fleets run on solvers that were good enough a decade ago. The gap between "a feasible route" and "the cheapest feasible route" is real money — fuel, hours, vehicles. QuGradient closes that gap with quantum optimization that holds up under your real constraints.

6%+
Routing cost reduction with RouteIQ
preliminary · vs current solver, on partner data
13.1%
Scheduling improvement in benchmark
preliminary · documented methodology
4
Products on one optimization core
15yr
Of optimization research behind it

Pilot

Regional LTL carrier · ~1,200 vehicles — 6.2% lower routing cost across 3,418 stops, every time-window and capacity constraint honored.

The IQ product family

Four products. One optimization core.

RouteIQ

Fleet routing optimization. Reduces routing cost against your current solver — measured on your data.

Beta6%+ · preliminary

DispatchIQ

Real-time scheduling and dispatch across constrained fleets and field-service crews.

Preview

FlowIQ

Workflow and throughput optimization for warehouse and hub operations.

Design partner

SemanticIQ

Semantic search and decision support over operational and logistics data.

Research-stage
See the products

How it works

We don't ask you to take the number on faith.

STEP 01

Connect your data

Historical routes, constraints, fleet and cost structure. Read-only to start — no rip-and-replace.

STEP 02

Benchmark on your data

We run QuGradient against your current solver on your own jobs, with a documented methodology.

STEP 03

See the delta

You get a clear read on cost, distance and time — and exactly where the savings come from.

STEP 04

Deploy what wins

Connect to your TMS and operations only once the benchmark proves out. Honest about what's beta.

The platform

The optimization core under every product.

One engine powers the whole family — and the families that follow. Hybrid quantum-classical and quantum-inspired solvers, where they measurably win; classical methods where they don't. We don't claim a quantum computer is in the loop when it isn't.

ExperiencePlanner UI, dashboards, configuration
Optimization servicesRouteIQ · DispatchIQ · FlowIQ · SemanticIQ
Solver orchestrationHybrid & quantum-inspired solvers · constraint handling
Data & integrationConnectors to TMS, fleet and operational systems
FoundationSimulator · benchmarking infrastructure · the QuMatrix research base

Why now

Quantum-optimized results, ready to deploy.

QuGradient is the deployable form of QuMatrix's logistics research: the algorithms are mature, the benchmarks are documented, and quantum-optimized routing is proving its value in pilots today — ready to run against your real constraints.

Proven science

Built on QuMatrix — 350+ papers and a decade of applied optimization across energy, logistics and beyond.

The research →

Measurable proof

RouteIQ in beta with design partners; every claim tied to a benchmark on real data, labeled honestly.

RouteIQ →

Ready to deploy

Bring a slice of your routing data and we benchmark quantum-optimized routing against your current solver — then connect what wins to your operations.

See the research →

Two ways to start

See it on your data.

Bring a slice of your routing data and we'll show you the delta in a 30-minute call — quantum-optimized against the solver you run today.