Dispatch & load coordination
Automates broker and check calls and matches drivers to loads, removing ~60% of a dispatcher's repetitive workload so each manages more trucks.
AI for transportation & logistics, on the paperwork and the phones.
Thin margins, manual paperwork, and non-stop status calls define mid-market logistics. We put AI on the documents and coordination — BOLs, PODs, quotes, dispatch calls, and freight audit — so your team spends time on the loads and relationships that make money.
Everyone's using it — few have mastered it. 96% of transportation teams use generative AI, but only 17% call themselves optimized, per Descartes.
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Documents and coordination.
AI reads, drafts, quotes, and audits the paperwork and communication that eat back-office and dispatch hours — the highest-volume, lowest-risk work in the operation.
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Margin is the case.
Trucking margins often run 2–3%. McKinsey puts AI-driven logistics-cost reductions at 5–20%; every hour of manual paperwork removed drops toward the bottom line.
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Optimized, not just adopted.
Nearly everyone uses AI; almost no one has it fully working. We're the implementation partner that closes that gap into production workflows.
Where AI fits in transportation & logistics
BOL / POD processing
Reads BOLs and signed PODs — even handwritten — into structured TMS fields, cutting manual document entry 80–90% and processing from minutes to seconds.
Rate & spot quoting
Reads inbound quote requests and generates spot quotes in seconds from your own pricing methods — brokers answer far more of the quote volume they used to miss.
Shipment-status comms
Answers 'where is my order' by querying the TMS/carrier for live status and ETA — deflecting the 30–40% of contacts that are status checks.
Freight audit & invoicing
Reads carrier invoices, matches them to contract terms and accessorials, and flags overcharges before payment — recovering a few percent of freight spend.
Demand forecasting
Forecasts demand and automates replenishment from usage and lead-time data, cutting forecast error and the capital tied up in excess stock.
How it works.
Start with the documents and calls. Usually BOL/POD processing or shipment-status comms.
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We target the manual layer.
Document entry, quoting, dispatch calls, and freight audit — the repetitive work draining thin-margin back-office and dispatch hours.
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We install it in your TMS.
The right models wired to your systems and carrier data, with humans handling the exceptions the AI flags.
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We train and measure.
Dispatch, CS, and back-office learn where AI fits their day; we track the hours and dollars it returns and expand.
This is for you if:
- A mid-market carrier, 3PL, distributor, or logistics operator.
- Manual paperwork and status calls drain thin-margin hours.
- You're feeling the dispatcher/driver and back-office squeeze.
This is not for you if:
- You want AI in autonomous, safety-critical vehicle control.
- You want it making high-cost decisions with no human review.
- You're not willing to change the back-office workflow.
Go deeper on AI for transportation & logistics
The guides and case studies behind this page.
In partnership with
FAQs
What is the best first use of AI in a logistics company?
BOL/POD document processing or shipment-status communications. Both are high-volume, document- and message-heavy, and reviewed on exceptions — so they return time immediately with no operational risk.
Is AI safe to use in transportation?
For paperwork, quoting, and customer communications, yes — a human handles exceptions and anything high-cost. It should never be in autonomous, safety-critical vehicle control.
Do we need to replace our TMS?
No. The fastest wins read documents and draft communications alongside your existing TMS; deeper integrations come later, once the first workflows prove out.