Smarter Auditing for Inbound Material Loads
Are You Getting the Material You Paid For?--
For companies that purchase aggregates — such as cement plants, asphalt operations, land development firms, and municipal governments — every load that arrives at your site represents both a cost and a risk.
The reality is simple: you don’t always receive what’s on the delivery documentation.
In the U.S., many organizations rely on digital ticketing platforms like HaulHub or Command Alkon to track and manage bulk material deliveries. These systems are excellent for streamlining logistics and documentation — but they don’t verify what was actually delivered to your plant or job site.
In other regions, similar records may take the form of paper tickets, handwritten delivery notes, or internal tracking systems. Regardless of the format, one thing is true:
A document tells you what should have arrived — not what did.
And that leaves room for costly issues:
- Trucks arriving only partially loaded
- Empty trucks showing up with a valid ticket
- Trucks dropping material en route before reaching the destination
- Duplicate ticket numbers used to mask missing loads
- Even internal theft — enabled by a lack of visibility at the gate
These problems result in real financial losses and inventory inconsistencies — regardless of how you track your deliveries.
Our approach introduces a smarter way to monitor inbound deliveries using automated Load Volume Scanning and Anomaly Detection technology. This allows buyers to verify what’s actually arriving at their site, regardless of the trucking company or ticket source.
Catch Problems Early with Load Approximate Estimate (LAE)
Even when trucks arrive without prior registration or a scan of their empty state, our system can generate what we call a Load Approximate Estimate (LAE). This estimate is based on visual and geometric features of the truck’s loaded profile — such as shape, size, and fill level. LAE provides a solid first estimate that helps flag suspicious deliveries.
This helps you spot anomalies automatically and in real time, especially with third-party haulers or suppliers that are harder to monitor.
Behavioral Anomalies Matter TooNot all issues are about load size. Some are about behavior. We flag suspicious patterns like:
- Very short site time (truck didn’t unload)
- Tarp still on when leaving
- Quick re-entries that may hide ticket duplication
These signals, combined with our Load Approximate Estimate (LAE), strengthen automatic anomaly detection — even without full registration.
Smarter Estimates That Improve Over TimeOur system becomes more accurate with use. We apply advanced machine learning models trained on thousands of real-world truckloads. These models learn how trailer shapes, load profiles, and visual cues relate to actual material volume.
As more data is collected, these predictions become increasingly refined — providing stronger validation, even for trucks without registration or an empty scan on file.
While this estimate may not be as precise as a full volumetric calculation, the margin of error is small enough to effectively detect delivery anomalies and protect your bottom line.
For the highest accuracy, we recommend registering your truck fleet and capturing empty truck profiles. This allows for true volumetric calculations with our Load Volume Scanner, which compares the loaded and empty scans to determine the exact volume of material delivered.
With this in place, you get high-confidence measurements per delivery. But even without it, LAE allows you to take immediate action and improve accountability across your supply chain.
The Bottom LineIf you’re managing inbound aggregates and relying solely on delivery documentation — whether digital or paper-based, there’s a good chance you’re paying for material that was never delivered. With automated load scanning and anomaly detection in place, you get:
- Confidence in every delivery
- Accountability from suppliers and haulers
- Reduced risk of loss or fraud
- Stronger inventory and cost control
Digital systems tell you what should have been delivered.
Our truck volumetric scanning solution tells you what actually was.