Motor carriers and trucking
One AI over your entire operation.
A chief of staff for your trucking company. It watches the load board, every truck, every driver, every invoice and every dollar, runs the busywork, reminds your team, escalates what matters and tells you everything.
The answer before the details
Dry van, reefer, roughly 3 to 50 trucks, built around your rules. Carriers that size are exactly where one or two people carry the whole back office in their heads, so the leverage is a layer over the twelve systems you already run rather than a thirteenth piece of software.
You do not need a thirteenth piece of software. You need one brain sitting over the load boards, email, phones, telematics, TMS, accounting and bank feed you already run, reading everything, connecting everything and acting on it under your rules.
Operating map
What breaks, and what Tensor Garden fixes first.
These are practical workflow patterns, not case studies. The exact sequence comes from the assessment and the systems already in place.
- 01
The operating day
What breaks
Milestone updates, rate con checks, check calls and dock detention all depend on a human remembering, around the clock.
What we fix
Confirmations go out before the day starts, the board is filtered against your radius, weights, shipper list and no-go cities, and the detention clock starts itself.
- 02
The escalation line
What breaks
A truck empty since 8 AM creates pressure to take a bad load.
What we fix
The agent hands your team everything it tried, with options, and lets a human make the judgment call. Your rules decide where the line sits.
- 03
Earning autonomy
What breaks
Turning an agent loose on freight decisions on day one is how these projects fail.
What we fix
It graduates the way a new dispatcher would: shadow, then suggest with one-click approvals, then run a phase on its own only after sustained measured accuracy, and it escalates when uncertain.
Common pain points
- Take a Saturday off and loads do not get booked. The company runs on you, and that is the ceiling on how big it gets.
- Your dispatcher is the system. If she is out, the operation loses its brain.
- Check calls never sleep, receivables slide toward 90 days, and the money picture is scattered across QuickBooks, the bank, the load board and a notepad.
Common projects
- Load lifecycle mapping, board to booking to delivery to payment
- Rate memory and negotiation leverage from your own history
- Truck and driver expected-versus-actual watch
- Receivables enforcement with aging and logged excuses
What to avoid
- Letting an agent take a desperation load instead of escalating to a human.
- Booking, bidding or negotiating before your floors and no-go rules are written down.
- Treating the AI as a headcount play instead of taking the grunt work off the desk.
Expected outcomes
- Loads confirmed before anyone is awake
- Nothing living in one person’s head
- Net-30 that stops becoming net-90
- The bleed visible per truck and per lane
Connect the problem to the right service
- AI AutomationThe underlying service: intake, routing, follow-up, reporting and document workflows.View service →
- Logistics and truckingThe industry page for dispatch, documents, vendor portals and reporting.View service →
- Business Operating SystemsThe connected workflow layer the agent needs underneath it.View service →
- Responsible AIWhere humans stay accountable and what we do not automate.View service →
Security and compliance caveats
- Founder Ash Vaja brings more than 20 years of experience in insurance and technology, holds CIC and TRS designations, and has completed two insurance-agency exits. Your rate history, shipper list and broker relationships stay yours. Deployment options are on-premise, a private tenant in your own cloud, or managed by us.
- Safety-sensitive and regulated operations keep human ownership. The agent does not act unsupervised on high-stakes calls.
What carriers ask before they call
What if the AI books a bad load?
It cannot book anything outside the rules you set, and it does not get full control on day one. Every phase starts in shadow mode where it only shows you what it would have done.
Is my rate data training somebody else’s AI?
No. Depending on the deployment you choose, your data lives on a machine in your building, inside your own cloud account, or under zero-retention agreements. Every account is opened in your name.
Do I have to replace my dispatcher?
No, and we would advise against it. The system handles the repetitive machine work. Your people handle judgment, relationships and exceptions.
Can it really tell me where money is going?
It connects your accounting, bank feed and load data, then breaks cost out per truck, per lane and per company, and surfaces maintenance trends, fuel spikes and lanes that lose money on every run.
What systems does it connect to?
Load boards, your email and phones, GPS and telematics platforms, your TMS, accounting and your bank feed. We build around the stack you already run.
We are a small fleet. Is this really for us?
Carriers running roughly 3 to 50 trucks get the most out of this, because that is exactly the size where one or two people carry the whole back office.
How the work is controlled
Your priorities set the work. You approve additional charges before extra work starts.
The assessment maps the whole stack, stabilizes the risk first, then builds the workflow layer. Nothing chargeable starts before your authorized decision-maker says so.
How we work, in fullMap the freight workflow before choosing tools.
One assessment across your industry workflow, IT stack and automation path. We identify what is urgent, what is risky, what is wasting staff time, and what can safely become a system.