SAMPLE: DACHSER Americas · Trucking Lane & Mileage Board

Trucking Lane & Mileage Board — Americas

Zip-to-zip lane distance, cost per mile and on-time performance across the Atlanta, Chicago, Miami and New York trucking network, with the Laredo–Monterrey cross-border corridor. One place for the questions the Trucking desk asks every Monday.

Prepared for Carrie

Department Trucking, Americas

Regional Head Office Americas Atlanta, GA

Issue September 2026

Network at a glance

Every tile recalculates from the lane-level fact table when a filter changes. Deltas are vs the prior period of the same length, or vs target where marked.

Lane map — four US hubs and the Laredo gateway

Arc thickness = shipments in the selected period · arc colour = on-time delivery. Hover a lane for zip-to-zip detail.

≥ 95% on-time delivery 90–95% < 90% (signal) low volume high volume

Zip-to-zip distance

The modification the Trucking desk asked for: pick two zips and the report returns road miles, transit days and a cost estimate from the lane matrix.

Origin zip

Destination zip

On-time delivery trend vs 95% target

Weekly on-time delivery %, with shipments per week beneath it.

Shipments by carrier

Contracted carriers ranked by volume in the selected lanes; on-time delivery shown beside each bar.

Lane detail — zip to zip

Sorted by shipments. Cost per mile is all-in linehaul or drayage rate including fuel.

Lane	Type	Miles	Shipments	$ / mile	OT pickup	OT delivery

Shipments by region & service

Trucking split into linehaul vs drayage. Switch Service to “All modes” to lay air & ocean alongside.

What this board answers

Three questions from the Trucking desk, each answered with a number from the filtered data above.

Ask the data

A natural-language layer over the same model. Ask in plain English, get a number and the panel it came from.

Which lane is hurting on-time delivery most, and how many shipments were late?↵

Private AI on your own server

The "ask the data" panel above is built to run on a GPU server inside your own network: an open-weight model over your own documents, with every answer citing the file it came from. No per-seat licence, works offline, and nothing leaves the building.

How it sits in your environment

One appliance-class server on your rack or in a secured closet. Your files are indexed where they already live; the model runs locally; answers come back with the source page attached.

What that means in practice

1
Your data only, on your hardwareAn open model over your own documents and exports. No third-party AI processor, no data-transfer agreement to review.
2
Every answer cites its sourceReplies point to the file and page they were drawn from, so people check the answer instead of trusting it blind.
3
No per-seat licenceThe whole team can ask questions. Cost is the server and our build, not a monthly number that grows with headcount.
4
Works offlineIf the internet connection goes down, the answers still come. Nothing depends on a vendor's uptime or pricing changes.