Logistics & Supply Chain

150 routes. 2,000 stops. One optimal plan.

kint sees all routes, all constraints, all time windows at once. Fewer kilometers, lower fuel costs, tighter schedules.

€1.4T

annual logistics costs in Europe

European Commission, 2023

28%

of fleet operating costs are fuel

IRU World Road Transport Organisation

15-25%

typical savings from route optimization

MIT Center for Transportation

When Complexity Exceeds Human Capacity

You're planning tomorrow's deliveries. 47 trucks, 2,847 stops, 6-hour time windows, EU driver regulations, varying vehicle capacities. By noon you have a plan that looks reasonable. But reasonable isn't optimal. The difference between your plan and the mathematical optimum is 20-30% in wasted kilometers. Every single day.

Scaling breaks spreadsheets

Above 50 stops, the number of possible routes exceeds what any planner can evaluate. Each constraint added makes it exponentially harder.

Re-planning is expensive

One cancelled delivery means re-doing the entire plan. Manual replanning takes hours. kint re-optimizes in minutes.

You can't measure what you're missing

Without a mathematical baseline, there's no way to know if today's plan is 5% or 35% from optimal.

Knowledge walks out the door

When your best planner is sick or leaves, planning quality drops. Mathematical models don't take vacations.

Comparison

Status Quo vs. With kint

Planning time

6 hours / day

12 minutes

Route optimality

Unknown, 'good enough'

Measured: 0.3% from proven optimal

Fuel costs

Baseline

-18% average reduction

Re-planning

3-4 hours per disruption

Under 5 minutes

Driver compliance

Manual checking

Guaranteed by constraints

Process

How It Works for Logistics & Supply Chain

Connect your route data

Databases, APIs, CSV, Excel, or your TMS directly. Stops, time windows, vehicle specs, driver rules.

kint builds the model

Variables, constraints, objective function. Your team reviews the setup. No mathematical expertise needed.

Solve and compare

kint finds the optimal routes. Compare against your current plan side by side.

Deploy or iterate

Use the plan directly, adjust constraints, or run what-if scenarios before committing.

Use Cases

What kint solves in Logistics & Supply Chain.

Route Optimization

Input

“Optimize delivery routes for 47 trucks across 6 countries”

Output

kint computes optimal routes respecting time windows, vehicle capacity, driver regulations, and real-time traffic patterns.

The complete plan is ready before trucks leave. Every route respects driver hours, vehicle capacity, and customer time windows. Changes propagate automatically across the full plan.

-23%

km saved

-18%

fuel costs

2 min

solve time

Inventory Optimization

Input

“Balance stock levels across 12 warehouses to minimize holding costs”

Output

kint determines optimal stock allocation per SKU and location, factoring in demand forecasts, lead times, and service level targets.

Stock moves to where demand is predicted. Overstock in one warehouse fills gaps in another. Safety stock levels adjust per SKU based on demand volatility, not fixed rules.

-34%

holding costs

99.2%

service level

-41%

stockouts

Demand Planning

Input

“Forecast and optimize procurement for seasonal demand shifts”

Output

kint combines demand prediction with procurement optimization to find the cost-minimal ordering schedule under supply constraints.

Seasonal spikes and dips are anticipated weeks ahead. Procurement orders align with predicted demand curves, reducing both emergency orders and excess inventory.

+27%

forecast accuracy

-19%

procurement cost

faster planning

∞

Your Problem

These are examples. kint is not limited to predefined use cases.

> Describe your problem. kint handles the math.

Try with your own problem

FAQ

Common Questions About Logistics & Supply Chain Optimization

Yes. kint accepts Excel, CSV, JSON, and direct database connections. If your TMS can export data, kint can work with it. API integration for automated workflows typically takes days.

kint re-optimizes when conditions change. A cancelled stop, a traffic delay, a new priority order. The solver finds the new optimal plan in minutes, not hours.

kint works at any scale. But the ROI is highest when complexity exceeds what a planner can manage manually. Typically above 20 vehicles or 100 stops.

Typical route optimization problems solve in under 5 minutes. Larger instances with thousands of stops may take longer. kint reports progress and intermediate solutions while solving.

For OEM Partners