API-first delivery
Integrate optimization into the systems teams already use for field operations, dispatching, or planning.
Quantum optimization platform
Optimization infrastructure for real-world operations.
Quantum Optimization API | Scheduling & Routing Solver | Qtangl
Qtangl turns difficult scheduling, routing, and resource allocation problems into API-driven workflows that return clear, constraint-aware plans.
Built for scheduling, routing, and allocation problems.
Designed for operations teams and developers, not research labs.
Hybrid workflows combine classical preprocessing with quantum-assisted search.
The problem
Business operations are harder to optimize than they should be.
Qtangl is built for the problems that still fall between manual planning and generic software. When scheduling and routing depend on changing constraints, teams need a solver stack instead of another dashboard.
Scheduling is still manual and fragmented across teams, tools, and spreadsheets.
Routing decisions become inefficient when constraints shift in real time.
Most optimization software is difficult to integrate into existing operations systems.
Generic AI tools can summarize data, but they do not reliably solve constraint-heavy combinatorial problems.
The solution
A quantum optimization API for real-world operations.
Submit scheduling, routing, or allocation problems through a single API.
Qtangl converts operational constraints into optimization-ready models.
Hybrid execution combines classical orchestration with quantum-assisted search where it helps.
Teams receive optimized plans they can review, compare, and act on quickly.
Constraint-aware outputs
Priorities, deadlines, dependencies, and capacity limits remain part of the optimization problem.
Operational clarity
Outputs are returned as practical schedules and plans rather than research artifacts.
How it works
Three steps from input to optimized plan.
01
Define the problem
Send jobs, locations, resources, and business constraints as structured JSON.
02
Run hybrid optimization
Qtangl prepares the model, runs the solver stack, and evaluates feasible plans.
03
Return an action-ready plan
Receive ranked schedules, routes, or allocations with method and cost metadata.
Use cases
Built for scheduling, routing, and allocation workflows.
Construction
Construction scheduling optimization
Coordinate crews, equipment, and site dependencies without rebuilding the plan manually every time conditions change.
Problem: Project managers juggle trade sequencing, inspection windows, and resource conflicts across multiple jobs.
Outcome: Qtangl returns a feasible schedule that respects precedence, crew availability, and time windows.
Value: Reduce idle crews, cut delay risk, and improve schedule confidence before work starts.
Logistics
Logistics routing optimization
Balance delivery windows, fleet capacity, and route efficiency with a single routing workflow.
Problem: Dispatch teams must react quickly to traffic, customer windows, and capacity constraints.
Outcome: Qtangl returns optimized route plans with stop order, assignment, and estimated cost.
Value: Lower miles traveled, improve on-time delivery, and increase fleet utilization.
Operations
Workforce allocation optimization
Match the right people and resources to the right jobs while respecting availability and skill constraints.
Problem: Schedulers often rely on tribal knowledge to assign labor across shifting demand and limited capacity.
Outcome: Qtangl ranks staffing plans that fit required skills, coverage targets, and utilization limits.
Value: Improve coverage quality, reduce overtime, and make staffing decisions faster.
API concept
Job submission in, optimized result out.
Developers define the problem in JSON, Qtangl runs the optimization workflow, and operations teams receive a plan with solution metadata they can review or feed back into existing systems.
Request
{
"type": "schedule",
"tasks": [
{
"id": "foundation",
"duration": 3,
"crew": "Crew A"
},
{
"id": "framing",
"duration": 4,
"crew": "Crew B"
},
{
"id": "inspection",
"duration": 1,
"crew": "Inspector"
}
],
"constraints": [
"foundation must finish before framing",
"inspection must occur after framing",
"Crew B unavailable on day 2"
]
}Response
{
"status": "success",
"solution": [
{
"task": "foundation",
"start": "2026-05-27T07:00:00Z"
},
{
"task": "framing",
"start": "2026-05-30T07:00:00Z"
},
{
"task": "inspection",
"start": "2026-06-03T09:00:00Z"
}
],
"cost": 12,
"method": "hybrid-qaoa",
"backend": "ibm_quantum_simulator"
}Early access
Bring Qtangl into your operations workflow.
Request early access to shape the first enterprise optimization workflows for scheduling, routing, and resource allocation.
Frontend-only MVP. This form captures intent locally for now.