SciTransfer
LogisticsBrain · Project

AI-Powered Automated Transport Planning Software to Reduce Logistics Costs and CO2

transportPilotedTRL 8

Imagine a super-smart digital brain that looks at thousands of possible delivery routes at once to find the absolute cheapest and fastest path. Instead of a person spending hours manually planning where trucks go, this software does it automatically in real-time. It's like having a GPS that doesn't just find one way, but optimizes the entire fleet's schedule to save fuel and time.

By the numbers
40%
cost optimization
90%
planning time reduction
21%
CO2 and fine dust reduction
80%
route planning automation
2-3
FTEs saved per hub
The business problem

What needed solving

Logistics dispatching is often manual, slow, and fragmented across multiple software tools. This leads to high operational costs, wasted fuel, and inefficient use of human resources.

The solution

What was built

A self-learning, cloud-based AI dispatch software (LogisticsBrain) with a standardized API for TMS integration and a CO2 reporting module.

Audience

Who needs this

FTL Freight ForwardersLTL Transport CompaniesLarge-scale Logistics Hub ManagersCourier Network Operators
Business applications

Who can put this to work

Freight Forwarding
any
Target: Full Truck Load (FTL) transport companies

If you are a freight forwarder dealing with complex manual dispatching—this project developed an AI core that automates 80% of route planning. This can save 2-3 employees per hub and reduce planning time by 90%.

Courier Services
enterprise
Target: Multi-hub delivery networks

If you are a courier service dealing with 50+ hubs and multi-day routes—this project developed a cloud-based software that optimizes costs by 40%. It handles LTL, FTL, and excess pallets in one system.

Supply Chain Management
mid-size
Target: Networked logistics providers

If you are a logistics provider dealing with high carbon footprints—this project developed a CO2 reporting tool and optimization engine that reduces emissions and fine dust by 21%.

Frequently asked

Quick answers

How much can this software reduce operational costs?

Based on available project data, the AI-based optimization engine can optimize costs by 40%.

Can this be scaled to large networks?

Yes, the AI core was extended to handle complex scenarios involving 50+ hubs and multi-day routes.

What is the licensing or IP model?

Based on available project data, the solution is offered as a Software as a Service (SaaS) model.

How does it integrate with existing IT systems?

The software uses standardized interfaces and APIs that have been successfully integrated with customer Transport Management Systems (TMS).

What is the timeline for implementation?

The project ran from June 2022 to May 2024, reaching a target of TRL 8 through pilot qualifications.

Consortium

Who built it

The project was led by a single German SME, Smartlane GmbH, which acted as the sole coordinator and partner. This 100% industry-led structure allowed for a direct focus on commercialization and rapid integration with customer TMS systems, avoiding academic delays.

How to reach the team

Contact Smartlane GmbH in Germany for SaaS licensing

Next steps

Talk to the team behind this work.

Request a demo of the LogisticsBrain AI engine

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