Plan parcel, postal and e-grocery delivery routes in the short window between order cutoff and loading. The TQrouting-powered solution optimizes thousands of daily stops in minutes and runs as an embedded engine inside your own environment, alongside your existing systems.
Request a demo session with our routing team. We solve a large-scale instance and walk through what the engine produced: route quality, runtime, and how each constraint was handled.
For teams evaluating a routing engine to license and deploy in their own environment, whether you run the fleet yourself or build routing into a platform your customers use.
The planning window is short by nature. Orders close late and vehicles must be loaded early at the depot, and the gap between the last order and the first loading can be as little as 20 to 30 minutes. Within that tight time limit, the solver still has to produce routes that respect customer time windows, vehicle capacity, driver hours and service-level commitments.
General-purpose optimization solvers handle small problems well, but as networks grow and constraints multiply, solution quality drops, and within 20 to 30 minutes they may not find a feasible plan at all. The cost surfaces as extra vehicles, longer shifts and missed delivery slots.
TQrouting applies across last-mile delivery. These are the operations where it makes the most difference.
Next-day and recurring delivery at high stop density, under tight time windows and service-level obligations.
Booked-slot delivery under narrow windows, shifting demand, with perishable goods and no room for delays.
Energy-feasible routing across any of these operations: battery range and charging handled in the same plan.
Request a demo session with our routing team. We solve a large-scale instance and walk through what the engine produced: route quality, runtime, and how each constraint was handled.
For teams evaluating a routing engine to license and deploy in their own environment, whether you run the fleet yourself or build routing into a platform your customers use.
Built for last-mile operators with:
Three things keep route quality high as the problem grows.
Our in-house ML-based decomposition and advanced parallelization preserve route quality as stop counts and constraints increase, where general solvers lose quality.
Produces dispatch-ready routes in short runtimes, fast enough to fit inside the window between order cutoff and vehicle loading.
Rules such as delivery-time priorities, driver shift limits and depot reload times are handled as constraints. During the day, missed deliveries and new pickup requests can be absorbed by re-optimizing the remaining plan.
The solution runs on TQrouting, Terra Quantum's vehicle routing engine. It combines AI and advanced mathematical optimization to solve large-scale vehicle routing problems, and is independently validated on the public CVRPLib benchmark, where it set 27 new best-known solutions.
Parcel and postal are the primary focus. The same engine applies wherever many stops are planned under time and capacity constraints, including e-grocery delivery and electric or mixed fleets. See the TQrouting page for the full range of applications.
No. TQrouting is a routing engine, not a TMS or a driver app. It runs inside your own environment and produces routes that are ready to dispatch.
Yes. You can evaluate it on your own routes and data, through TQrouting Early Access.
TQrouting is licensed annually. Pricing depends on your deployment scope, which we define together in a short call.
Standard hardware, from a laptop to a server, on Windows, macOS or Linux. Your routing data stays inside your own environment.
Request a demo session with our routing team. We solve a large-scale instance and walk through what the engine produced: route quality, runtime, and how each constraint was handled.
For teams evaluating a routing engine to license and deploy in their own environment, whether you run the fleet yourself or build routing into a platform your customers use.
