USE CASE · 01
Document processing
Bills of lading, proof-of-delivery scans, customs declarations, CMRs: extracted, validated, and filed. The messy 30% that off-the-shelf OCR drops gets routed to a human, not lost.
AI for Logistics · PXT AI
AI for logistics, built by people who ship software.
Route optimization, document processing, inventory agents, inbound order handling. Built on your stack, not a vendor SaaS. We deploy, document, and hand off. Your team runs it.
-87%
doc processing time (client result)
3 wks
prototype to production-ready
18 mo
in production and running
Use cases
Where AI pays off in logistics.
Logistics operations run on documents, exceptions, and time-sensitive decisions. These are the six areas where AI earns its keep fastest. Each one is a workflow we have shipped.
USE CASE · 02
Exception flagging
Shipment delays, weight discrepancies, missing signatures, incomplete customs data. The AI reviews every record and escalates only what needs a human decision. No more end-of-day inbox triage.
USE CASE · 03
Route optimization agents
Pull live capacity, fuel cost, and delivery-window data from your TMS. Suggest optimal carrier-lane pairings. Keep a human in the final approval seat.
USE CASE · 04
Inventory and demand agents
Monitor SKU velocity, flag reorder thresholds, draft purchase orders for review. Works against your WMS or ERP. No rip-and-replace required.
USE CASE · 05
Inbound email and order handling
Customer order emails, carrier rate requests, booking confirmations. Classified, extracted, and routed to the right system in seconds. Replies drafted for a human to send.
USE CASE · 06
Carrier and vendor communication
Automated status-update drafts, shortage notifications, and detention-charge disputes. The AI writes. Your ops team approves and sends.
Looking for AI document processing specifically? See the dedicated page or explore AI workflow automation for cross-functional builds.
Case study · Logistics SaaS
Queue cleared in week one. Still running 18 months later.
A mid-market logistics SaaS had a 14-person manual review queue for incoming shipping documents: bills of lading, customs forms, proof-of-delivery scans. Days-long backlog. Enterprise clients complaining. Standard OCR vendors could handle the clean 70%. The messy 30% bounced back to humans every time. We built an LLM pipeline that handles the hard cases and flags only the genuinely ambiguous records for a 3-person exception team. The queue cleared in week one.
-87%
document processing time
3 weeks
to a working prototype
18 months
in production and running
We'd written the budget for a vendor SaaS. They convinced us to spend a third of that on a prototype first. The prototype showed us the vendors couldn't handle our messy 30%, and gave us a system that could. Eighteen months in, it's still running.
VP Engineering, logistics SaaS
Our process
Diagnose. Roadmap. Build. Hand off.
Four phases. Humans in the loop at every step. Nothing ships without a working prototype first.
01
Diagnose.
We spend a week in your actual workflows: your TMS, your email queues, your review queues. We find the highest-volume, lowest-tolerance-for-error bottlenecks. Most teams have one costing 20+ person-hours a week.
02
Roadmap.
You get a prioritized build list with effort, timeline, and expected outcome per item. We flag the ones where AI is not the right answer. Sometimes a process fix or a cheaper tool gets you there.
03
Build.
Fixed scope, capped budget. A 3-week prototype proves it works on your real documents before the production build starts. No surprises.
04
Hand off.
Full documentation, an eval harness, a runbook, and a training session. Your team can maintain it without us. Humans stay in the loop on every exception path.
Pricing
Fixed scope. No surprise invoices.
Single-workflow logistics builds typically run in the same range as our standard workflow automation. Capped budget. A prototype phase before any production commitment comes first.
Workflow Automation Build Starts at $10,000 6-10 weeks typical for logistics builds
Most single-workflow builds run $10,000-$30,000. We quote a budget cap before we start, bill against actual work, and never exceed the cap without your written sign-off. Logistics document pipelines have a 3-week prototype phase built in. You see it working on your real documents before we build for production.
Need a broader look at options? See full workflow automation pricing
Frequently asked
Questions before the contract.
Will it integrate with our TMS or ERP?
Almost certainly yes. We have built integrations against SAP, Oracle TMS, TMW, McLeod, 3G TMS, custom internal systems, and flat-file or API feeds. If your system has an API or an email-out trigger, we can connect to it. If it is truly locked, we can build a UI-layer integration. We will tell you on the first call whether your stack is one we have seen before.
How do you handle bad scans (crumpled BOLs, faded stamps, low-resolution PDFs)?
This is the core problem we built for. Standard OCR vendors fail on the messy 30% of logistics documents: the ones that are damaged, skewed, or multi-page with mixed formats. Our pipeline uses AWS Textract for clean documents and a fine-tuned vision model for the hard cases, with a confidence threshold that routes anything below it to a human reviewer rather than processing it silently. The logistics-doc-pipeline case study had an 89% straight-through rate on documents the previous vendor was bouncing entirely.
Who maintains it after you hand off?
Your team, with our support. Every system we deliver includes a runbook, an eval harness with test cases drawn from your real document history, and a monitoring dashboard. We run a 30-day post-launch review and are available for a monthly retainer if you want ongoing model tuning as your document mix changes. Most clients run independently after 60 to 90 days.
How long does a build take?
A single-workflow build (document processing or exception flagging) typically runs 6 to 10 weeks: 3 weeks for a capped prototype and 3 to 7 weeks for the production build, depending on integration complexity. Multi-workflow rollouts are phased. We never try to ship everything at once.
What if we already have a vendor handling some of this?
Good. Tell us what it is handling well and where it falls down. We regularly work alongside existing OCR or RPA vendors, filling the gaps they can't cover rather than replacing them wholesale. If a full replacement makes more sense on ROI, we'll show you the numbers.
Ready to clear the queue?
Stop reviewing documents by hand.
Tell us where your team is losing the most time. We'll tell you whether AI is the right fix and what it would take to build.
No deck · No demo · No sales pressure