Industry
AI automation for logistics and fulfillment companies buried in quote requests, tracking questions, delivery paperwork and carrier invoices.
Sound familiar?
Logistics is run on email, phone calls and documents more than most people outside the industry realize. Shippers send quote requests in free text. Customers want status updates on every load. Drivers send proof of delivery as phone photos. Carrier invoices arrive as PDFs that need checking against rate confirmations. Each step is simple, and there are thousands of them.
AI automation for logistics focuses on that volume. A quoting workflow can read an inbound request, pull out lanes, dates, weights and equipment type, look up your rates or a market source and prepare a quote for a person to send. A customer support agent can answer tracking questions from TMS and visibility data, and only pass on the exceptions. Document processing turns PODs, BOLs and carrier invoices into structured data, matches them to loads and flags anything that does not reconcile.
For 3PLs and fulfillment centers, the work is often in integrations: connecting each new client's Shopify, WooCommerce or ERP to your WMS, mapping SKUs and keeping inventory in sync. We build those as reusable API integrations so onboarding the next client is faster than the last.
We are realistic about where AI fits. Rate decisions, claims and anything involving safety or compliance stay with your team. The automation prepares the information and gets out of the way. Most projects start with one workflow that can be measured, such as quote turnaround time or touches per load, and expand from there.
The problem
Freight brokers, 3PLs, fulfillment centers and small carriers have different business models, but their office teams spend their time on a similar set of tasks.
Requests arrive by email, portal and phone, with lanes, dates and freight details written however the shipper likes. Someone reads each one, checks rates and capacity, and replies. The fastest reply often wins the load, and slow quoting quietly costs business.
Shippers and consignees want to know where their freight is. Even with visibility tools in place, much of the day goes on checking the TMS, calling drivers or carriers and writing updates. Exceptions such as delays and missed appointments get mixed in with routine questions.
PODs, BOLs, lumper receipts and accessorial documents come back as photos, scans and emails. Billing cannot happen until they are matched to the right load, so cash flow depends on how fast someone can file paperwork.
Carrier invoices need checking against rate confirmations and agreed accessorials. Without time to check every one, overcharges slip through, while disputes take hours of email.
For 3PLs, every new client means connecting their store or ERP, mapping SKUs and units of measure, and setting up order and inventory feeds. Done by hand, it is slow and fragile.
Booking dock appointments, confirming pickup windows and onboarding new carriers with insurance certificates, W-9s and authority checks all run through email and portals. Each one is small, but together they keep dispatchers on the phone instead of solving problems on loads that are actually at risk.
Each of these is a good fit for automation with human review. The goal is fewer touches per load and fewer emails per order, not fewer people who understand the freight.
Carrier selection on high-risk loads, claims decisions, hazmat handling and anything tied to driver safety or hours-of-service compliance should stay with experienced people. AI is useful for gathering the facts and drafting the email, but those calls carry real liability. We build automations that make the right person faster, not ones that act without them.
Where we start
Inbound quote emails are parsed into origin, destination, dates, weight, equipment and special requirements, enriched with your lane history or rate tools, and turned into a draft quote for a broker or rep to approve.
Status questions by email or chat are answered from TMS and visibility data. Proactive updates go out at key milestones, and delays or missing check-calls are escalated to a dispatcher.
Delivery documents from drivers and carriers are read, matched to the load and attached in the TMS, with missing signatures, exceptions or shortages noted so billing can move the same day.
Carrier invoices are compared with rate confirmations and approved accessorials. Matching invoices are queued for payment; mismatches are flagged with the difference and supporting documents.
Reusable connectors for Shopify, WooCommerce, Amazon and common ERPs, with AI-assisted SKU and unit mapping that a person confirms, so new clients go live faster.
On-time performance, dwell, margin per load and order cycle times compiled into a daily or weekly summary for managers and key customers.
Integrations
McLeod, MercuryGate, Rose Rocket, Revenova, Tai and Descartes, through APIs, EDI or scheduled exports.
Extensiv (3PL Central), ShipHero, Deposco and NetSuite WMS for orders, inventory and shipment confirmation.
project44, FourKites, Trucker Tools, Macropoint and carrier APIs for location and milestone data.
Load tenders, status messages and invoices (204, 214, 210) through your existing EDI provider, alongside email for partners without EDI.
Shopify, WooCommerce, Amazon and ShipStation for 3PL clients' orders and tracking.
QuickBooks, Xero and NetSuite for invoicing, carrier payables and margin reporting.
FAQ
It handles typed fields well and handwriting reasonably, depending on image quality. Signatures, stamps and exception notes are detected and flagged rather than interpreted, and low-confidence documents go to a person. We test on a sample of your real documents before go-live.
No. It gathers the details, pulls your lane history and any rate tools you use, and drafts a quote. Your broker or rep decides the price and sends it, unless you choose to auto-send within rules you define.
It can only be as accurate as the data behind it. Where tracking is missing or stale, the agent says so and escalates instead of guessing. Often the project also shows where data gaps are, which is useful on its own.
We use scoped API credentials, business-tier model APIs that do not train on your data and keep records in your systems where possible. Customer-facing agents authenticate the user and only show shipment data belonging to that customer's account, and we test those boundaries before launch. If contracts require specific hosting or data locations, we design for that.
Usually. Many older systems support EDI, database access or scheduled exports we can build on. We assess this early and tell you if a limitation would make a workflow unreliable.
Tell us which TMS or WMS you run and where your team spends the most time on email and paperwork. We'll propose a first workflow and how we'd measure whether it worked, whether that is quote turnaround, days to invoice or emails handled per dispatcher. A sample of real quote emails, PODs or carrier invoices is the fastest way for us to show you what extraction and matching would look like on your own paperwork, before you commit to a build.
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