Industries
Logistics software development and AI agents for trucking companies
Your dispatcher checks the port portal four times a day. Rate confirmations get re-keyed into the TMS. You find out about a last-free-day from the demurrage invoice. We build the software and the AI agents that do that work inside the systems you already run — and we prove the first one in two weeks.
If this sounds like your operation, you're in the right place
Trucking runs on software that does not talk to itself. The TMS knows the load. The port knows the container. The steamship line knows a different last-free-date than the port does. Your customer's portal knows the PO. The only thing connecting them is a person with four browser tabs and a phone.
That person is expensive, and the work is not why you hired them. Every hour a dispatcher spends checking a website is an hour they are not moving freight. Every rate con typed by hand is a chance to bill the wrong number. Every missed last-free-day is a demurrage bill you did not need to pay.
Most of what we find at trucking and logistics companies is not an AI problem. It is two capable systems that do not exchange data, with a human standing in the gap. Sometimes the fix is a plain integration. Sometimes it is an AI agent that reads the documents, watches the portals, and tells a human only when something needs a decision. We build both, and we tell you which one you need before you pay for either.
The hero use case: container and last-free-day monitoring
A Houston trucking company moves import containers out of Port Houston. Their team tracked 600 to 700 containers a month by checking port and steamship-line websites by hand, reconciling conflicting last-free-dates, and hoping nothing slipped.
We built a monitoring system that sits inside the software they already used. It reads container status from the tracking API, reconciles the port's last-free-date against the line's, and sends dispatch a daily digest plus alerts when a date moves or a container needs attention. Exceptions go to a person. Routine status does not.
It runs across three systems: their TMS (TruckMate), the tracking provider (Vizion), and Microsoft Teams. They own the code, the runbook, and the hosting, and keep us on a Managed support plan to fix it when a port changes its website or a vendor changes an API.
Logistics software development for carriers, brokers, and 3PLs
Each of these is an AI agent or an integration, and each one moves a line on your P&L. We name both so you can judge the value before we build.
Check-call and status-update agent. Pulls location and ETA from ELD/telematics and the TMS, updates the customer portal or sends the status email, and flags loads that are running late. Systems: TruckMate, McLeod, Motive/Samsara, customer portals. P&L line: dispatcher hours per load; on-time reporting that protects the account.
Rate-con and BOL extraction into the TMS. Reads rate confirmations, bills of lading, and PODs from email and scans; creates or updates the load in the TMS; flags mismatches between the rate con and the invoice. Systems: email, TMS, QuickBooks or your accounting system. P&L line: billing errors, days-to-invoice, back-office hours.
Container, PO, and last-free-day tracking. The pattern above, adapted to your ports, lines, and TMS. P&L line: demurrage and per-diem avoided; dispatcher hours.
Driver-document capture. Collects and files CDL, medical card, insurance, and onboarding documents; alerts before expirations; feeds the compliance folder. Systems: TMS, driver app, shared drive. P&L line: compliance labor; audit exposure.
AR follow-up agent. Watches aging, sends the reminder sequence your collections person would send, escalates to a human at the threshold you set. Systems: TMS billing, QuickBooks, email. P&L line: DSO; cash cycle.
The weekly owner report. Pulls loads, revenue per mile, deadhead, on-time rate, and AR aging into one report you actually read. Systems: TMS, ELD, accounting. P&L line: the decisions you make faster because the numbers are in front of you.
Human review stays on every critical decision — a disputed rate, a customer-facing message with a problem in it, anything touching money — until the agent has run in parallel long enough to earn your trust.
Visibility first, then predictive analytics in supply chain operations
Most owners we meet do not have a forecasting problem. They have a visibility problem. The data to answer "which lanes lose money" or "which customers pay late" exists across the TMS, the ELD, and the accounting system. It has never been in one place.
That is the order we work in. First, the data foundation: a clean, automated feed from each system into one store, with the owner report on top. Then, once the numbers are trusted, the predictive layer earns its place: ETA prediction from historical dwell times, demurrage risk scoring on inbound containers, lane-level margin forecasting, and the exception alerts that come from all three.
Predictive analytics in supply chain work fails when it is built on data nobody trusts. We build the trust first. It is less exciting and it is the reason the dashboard gets used.
Why not just buy the TMS add-on?
Sometimes you should. Every TMS vendor now sells an AI feature, and if it does what you need inside the system you already pay for, take it.
Three reasons carriers call us instead:
- The work crosses systems. The add-on knows the TMS. It does not know the port, the line, the customer portal, or your accounting system. The work you want done lives between them.
- Nobody is accountable when it breaks. A port redesigns its website. A line changes its API. A vendor deprecates a feature. With a TMS add-on you file a ticket. With us, it is our job to fix it, with a response time in writing and monthly engineering hours already in the plan.
- You want to own it. Everything we build transfers to you: source code, runbook, hosting, vendor accounts. If we disappear tomorrow, your system keeps running and any engineer can pick it up.
How we decide what to build first
We do not start by building. We start with a two-day AI Readiness Assessment on site at your operation.
Day one, we walk your dispatch, billing, and compliance workflows with the people who do them, not only the people who manage them. Day two, we score every use case we found on two axes: P&L impact and risk. What we measure: revenue, margin, labor hours, cash cycle, and error cost.
You leave with a ranked backlog you keep, whether or not you work with us again. Then we build the number-one use case in two weeks against success criteria we agree on together. If it misses the mark, you don't pay for the build, and you keep it either way.
The assessment starts at $10,000 and is credited in full against your first workstream.
What it costs
- AI Readiness Assessment: from $10,000, two days on site, credited against the first workstream.
- Build workstreams: fixed fee, $10,000–$70,000 each depending on the systems touched, data quality, and number of integrations. Quoted on the call, not by the hour.
- Managed AI: from $600 per month. Three plans. Essential ($600) covers patching, a daily health check, two engineering hours a month, and next-business-day response on critical issues. Managed ($1,200), the plan we recommend, adds proactive monitoring and alerting, five engineering hours a month, and priority-one response in four business hours. Premium ($2,200) adds after-hours on-call and ten hours. Twelve-month term, billed monthly.
Prices verified September 2026. Full detail on the pricing page.
Why Vorsa Logic
Business goals first. Every use case is mapped to a P&L line and ranked by measurable ROI and risk before we write code. If a plain integration beats an AI agent, we tell you.
Built into what you already run. TruckMate, McLeod, Vizion, Motive, Samsara, QuickBooks, Teams. No rip-and-replace. One client's container system runs across three of them.
Yours to keep, ours to run. You own the code, data, and accounts. We stay on with a managed plan so it keeps working when the port, the line, or the vendor changes something.
Founder-built by Jonathan Klein and Chip Ray, based in Houston. Insured: cyber liability, technology E&O, and general liability.
What happens after go-live
Software that watches other companies' websites and APIs breaks when those companies change things. That is not a flaw in the plan; it is the plan. Our managed plan covers it: we monitor the system, we fix it when a vendor changes an API or a port redesigns a page, and we include engineering hours each month for the next improvement. On the Managed plan, priority-one response is four business hours; Premium adds after-hours on-call.
Frequently asked questions
TruckMate, McLeod, and the major cloud TMS platforms with an API. If your TMS has no API, we work from its exports and reports, and we tell you up front what that limits. Our first logistics build was TruckMate plus Vizion for container tracking.
The assessment is two days. The first use case goes into production in two weeks. Larger workstreams are scoped in weeks, not quarters.
The assessment starts at $10,000 and is credited against the first workstream. Build workstreams are fixed-fee, $10,000 to $70,000 each, depending on systems touched and data quality. Managed plans run $600 to $2,200 a month.
No. We build inside and around the systems you already run. If your TMS is the problem, we will say so, but that is rare. The problem is almost always what sits between the TMS and everything else.
Yes. We are based in Houston, and our first production logistics system tracks import containers through Port Houston. We work with carriers anywhere in the US; the on-site assessment is in person in Texas and the Gulf Coast and remote elsewhere.
We fix it. That is what the managed plan is for. That client's system watches ports and steamship lines that change their pages without notice; keeping it running is part of the service, with a response time in writing.
Have a portal your team checks by hand?
Book a two-day assessment. You get a ranked list of what is worth automating, scored by P&L impact and risk, and we build the top one in two weeks.
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