Move freight forward with confidence
Your team already knows how to run a reliable operation. IntelliTrans gives them the clarity, tools, and support to do it with greater confidence and control.
Rail is one of the most cost-effective modes for bulk freight. A single railcar can move the equivalent of three to four truckloads, and line-haul rates on bulk corridors typically run 30 to 50 percent below equivalent over-the-road costs, according to industry benchmarks. But that cost advantage erodes quickly when you cannot see what is happening to your fleet.
The challenge is structural. Rail networks are complex. Each shipment passes through multiple carriers, interchanges, and switch schedules. A single handling error at an interchange, an undetected out-of-route movement, or a car sitting idle past its free time can compound into real financial exposure. Demurrage rates on Class I railroads typically run $100 to $200 per car per day, escalating to $300 or more for extended delays, per industry benchmarks. For a shipper managing dozens or hundreds of active cars, the math adds up fast.
The traditional approach to this problem is manual monitoring: teams watching exception reports, chasing carrier updates, and reacting after something has already gone wrong. It works, up to a point. But it puts your team in permanent firefighting mode and leaves money on the table that proactive foresight would recover.
This is where predictive intelligence changes the equation. Rather than surfacing problems after they occur, it surfaces the signals that precede them, so your team can act before production schedules or customer commitments are affected.
The predictive capabilities built into IntelliTrans TMS are not standalone modules. They are embedded in the workflows your team already uses, surfacing actionable intelligence at the moment decisions need to be made. Here is what each capability does and what it means for your operation.
Railroad handling errors are common. Cars get misrouted, waybills get incorrect instructions, interchange handoffs go wrong. Most shippers find out when a customer calls or when a car fails to arrive on time.
IntelliTrans TMS uses predictive models built on 30 years of rail movement data to detect anomalous behavior as soon as a car begins deviating from its expected route, often before the railroad itself identifies the issue. The result is earlier intervention, faster carrier resolution, and significantly reduced transit time loss. On average, IntelliTrans customers identify 90 misrouted cars per month through this capability alone.
What this means for your team: You stop chasing problems and start solving them before they become delays. Your operations team gets to work the exception before it becomes an incident.
Not all exceptions are equally urgent. A car running two hours behind schedule on a long-haul lane needs different attention than a car sitting idle at an interchange three days before a production cutoff.
IntelliTrans TMS predicts the expected trip plan for each active shipment and flags deviations in real time, ranked by severity and impact. Your team's attention goes to the shipments that matter most, and the IntelliTrans operations team works directly with carriers to resolve flagged issues before they escalate. This prioritization discipline is what separates proactive operations from reactive ones.
Static ETAs are one of the most persistent sources of planning friction in rail freight. When an ETA is wrong, production schedules shift, customer commitments get missed, and your team spends time recalibrating rather than executing.
IntelliTrans TMS generates dynamic ETAs for every active railcar, continuously updated based on weather conditions, network congestion, switch schedules, carrier performance patterns, and real-time car location data. This degree of ETA confidence allows you to remove padding from fleet sizes and delivery planning, which directly reduces carrying costs and improves asset utilization. IntelliTrans customers have seen fleet cycle time decrease by 14 percent as a result.
What this means for your team: You plan against ETAs you can trust. Your commercial team quotes confidently. Your production team schedules accurately.
Railcar fleets are expensive to carry. Whether you own or lease, every car that is sitting idle rather than turning productive cycles is a cost you are absorbing without benefit. But undersizing your fleet creates the opposite risk: not enough cars when demand spikes or transit times lengthen.
IntelliTrans TMS runs thousands of what-if simulations based on probabilistic models drawn from your actual shipment history, seasonal patterns, and transit variability. The output is a fleet size recommendation that minimizes carrying cost while maintaining adequate supply coverage, even under adverse conditions. This is not a spreadsheet exercise. It is a data-driven discipline that gives your leadership team a defensible basis for fleet decisions.
Freight spend is one of the largest controllable costs in bulk operations. Accurately forecasting what future shipments will cost, before you commit to a production schedule or a customer price, requires more than a rate lookup.
IntelliTrans TMS uses predictive models built on historical shipment and rate data to estimate freight costs for planned moves with a high degree of accuracy. Your commercial team can quote with confidence. Your finance team can build spend forecasts that reflect actual likely costs rather than best-case assumptions. And your operations team gets a tool to validate carrier invoices against predicted costs, tightening audit discipline at the same time. IntelliTrans customers see accessorial cost reductions of 20 to 25 percent and line-haul rate improvements of approximately 1 to 2 percent through tighter freight audit integration.
When a railcar goes bad order and is pulled for repair, it disappears from active planning. Most teams simply write it off the schedule until it reappears. That uncertainty cascades into fleet sizing assumptions, production planning, and ETA commitments.
IntelliTrans TMS predicts bad order repair duration based on historical repair data for the relevant car type, repair location, and maintenance provider. That prediction feeds directly into the dynamic ETA for the car, giving you full visibility of your fleet even through repair cycles. You plan against reality, not assumptions.
Predictive models are only as good as the data behind them. A model trained on two years of shipment data will catch common patterns. A model trained on 30 years of rail movement data, across every Class I railroad and the full range of bulk commodities, catches the patterns that only appear in edge cases: the interchange that slows down in winter, the switch schedule that changes around commodity cycles, the carrier performance signature that precedes a service deterioration before it is officially reported.
This is the compounding advantage of depth. IntelliTrans manages approximately 38 percent of North American bulk rail freight, which means the models reflect a breadth of operating conditions and carrier behavior that no shipper could replicate independently. When your team acts on an IntelliTrans alert, they are acting on intelligence drawn from one of the largest rail freight datasets in North America.
38% of North American bulk rail freight managed by IntelliTrans. 90 average monthly misrouted cars identified per customer. 14% fleet cycle time improvement. 23% reduction in demurrage costs. (Source: IntelliTrans internal data. Results may vary.)