IndustryLogistics and transportation

AI systems for logistics and transportation.

The workflow pattern we see in this industry, and what we would build for it.

The workflow patternEvery handoff is manual

RFQ arrives

A shipper emails a quote request. A rep re-keys the lane, checks rates, and starts the clock.

Rate worked up

Pricing is assembled from rate sheets, spot boards, and memory. The quote takes hours when the shipper expects minutes.

Load dispatched

Dispatchers match loads to drivers by hand across hours-of-service, location, and equipment. Utilization is left on the table.

Status chased

Customers call for updates. Reps chase check calls and paperwork instead of the next load.

What we would buildNamed deliverables

A quote and dispatch desk agent.

An agent that reads inbound RFQs, drafts the quote with target margin by lane, proposes driver and load matches, and answers status requests from live data. Dispatch keeps the final say on every load. The agent removes the re-keying and the check calls.

10 to 14 weeks from kickoff to a live production system. We stay through adoption.

Named deliverables

Eval harness

Checks agent outputs against a test set before release.

Reliability gates

Hard checks the system must pass before it ships.

Live production system

The working system in your stack, not a report.

Adoption Mile

To the 70 percent weekly-active bar by day 90.

Industry ranges · Not ClearForge resultsIllustrative rows

Rep time spent on quote follow-up
About 40 percent
Illustrative
Dispatcher time on manual routing
20 to 40 percent
Illustrative
Margin lift from faster quotes
Varies by lane mix
Illustrative

Ranges are industry observations for orientation. They are not ClearForge results. Our results live on the proof page.

See the proof

Start where every engagement starts. The fixed-fee Diagnostic maps this workflow in your ops center in 2 weeks.

Starting point · Forge Diagnostic