Smartlane

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Munich
,
Germany
https://smartlane.de/en/

Smartlane Transport Inteligence offers a fully automated way to optimize general cargo logistics incl. – Automated dispatching even with complex restrictions – Self-learning optimization of general cargo routes – What-if analyses in transport simulations Complex requirements are no problem for Smartlane Transport Inteligence (STI). STI yields an optimal combination of deliveries and pick-ups, most efficient loading despite incomplete shipment data subject to territory specifications, vehicle restrictions and a wide variety of loading equipments. Smartlane finds the best solution based on over 250 planning parameters. On top of that, STI learns for future transport planning and completes your data.

Active
Active
Active
Transportation
General Information
Status
Active
City (Headquarter)
Munich
Country
Germany
FTE’s
30
Employees
Founding Date
27/7/2015
Funding ($)
$
7000000
Phone
+49 (0) 176-43457959
Contact Email
lubos@smartlane.de
Founder
Founders
Status
Active
City (Headquarter)
Munich
Country
Germany
FTE’s
xxx
Employees
Funding ($)
$
xxxxxxx
Phone
xxxxxxxx
Founder
Founders
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Techsegment
Software
Artificial Intelligence
Machine Learning
Market Sub-Segment
Planning
Transportation
Last Mile Delivery
Sustainability Sub-Segment
No items found.
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Techsegment
xxxxxx
Sustainability Sub-Segment
xxxxxx
Market Sub-Segment
xxxxxx
Description
Smartlane Transport Inteligence offers a fully automated way to optimize general cargo logistics incl. – Automated dispatching even with complex restrictions – Self-learning optimization of general cargo routes – What-if analyses in transport simulations Complex requirements are no problem for Smartlane Transport Inteligence (STI). STI yields an optimal combination of deliveries and pick-ups, most efficient loading despite incomplete shipment data subject to territory specifications, vehicle restrictions and a wide variety of loading equipments. Smartlane finds the best solution based on over 250 planning parameters. On top of that, STI learns for future transport planning and completes your data.
Company USP
– Self-learning algorithm – Over 250 planning parameters – Cooperation with most TMS providers & easy integration via API
Problems Solved
– Automation of manual dispatch – problem: lack of skilled dispatchers, stressful night shifts make the job unattractive – Dispatching up to 20% more goods with existing vehicle fleet - problem: high fuel cost, pressure on reduction of CO2 emmissions, lack of truck drivers
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Description

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Company USP

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Business Model
B2B Software
Target Customers
Logistics companies with LTL focus as well as industry & trading companies with own dispatching (focus on LTL)
Reference Customers
Hartmann International, Niedermaier amm Logistics, Emons
Operating Geographies
Germany
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Business Model
xxxxxx
Target Customers
xxxxxx
Reference Customers
xxxxxx
Operating Geographies
xxxxxx
For more details on this startup, you must register for a startup base account
Attachments
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