The Technology Behind Precision

We fly an RTK-equipped DJI Mavic 3 Enterprise. RTK — Real-Time Kinematic GPS — uses a fixed base station that broadcasts position corrections to the drone in flight, pinning every photo to a position accurate to roughly 1 centimeter horizontally and 1.5 centimeters vertically. That cm-level positional foundation is what lets us deliver month-over-month change detection inside 1.5% on undisturbed piles, with absolute volumes landing within 2-3% of survey-grade ground truth. A non-RTK consumer drone, by comparison, typically runs 5-15% on the same workflow.

Every flight is conducted by an FAA Part 107 certified pilot under $1M of liability coverage. Flight planning is computed per site so photo overlap is sufficient for reconstruction and ground resolution is fine enough to resolve pile surfaces.

Note: stockpile volume is a relative measurement. We measure the base of the pile and the top of the pile in the same flight, with the same RTK lock, and we re-measure the same site month after month with the same equipment and workflow — so systematic position error largely cancels between flights. That cancellation is exactly why the month-over-month delta is tighter than the absolute measurement, and why the drift in your inventory is detectable above the measurement noise.

Once the photos land, our processing pipeline takes over. Each job runs on its own isolated processing environment — your data never shares CPU or memory with another customer's flight. The pipeline turns 200+ overlapping aerial photos into a 3D model of your site tied to real-world coordinates.

The work is the standard photogrammetry sequence: solving where every photo was taken from, computing depth at every pixel, and stitching the result into a continuous textured surface. The math is well-established and the same approach used for survey-grade mapping — what matters for you is that the output is a measurable 3D model, not a guess.

From the 3D model we build a height map — essentially a heat map of how high every point on your yard is above the surrounding ground. Pile heights are isolated from ground level by filtering out the lowest points around each stockpile footprint, fitting a base surface, and measuring everything above it.

Volume is then computed by integrating the height grid over the pile footprint: for each grid cell inside the boundary, we know the area and the height above the base, and the product of the two summed across the whole pile gives us the cubic yards. The math is the same math a surveyor would do with a tape measure and a calculator — just on millions of points instead of three.

Cubic yards become tons via material-specific density. The platform stores per-material density values for every material on your site — concrete sand, washed gravel, #57 stone, RAP, and so on. Defaults are sourced from typical aggregate density references, but every density is editable per company, because your quarry's #57 stone may not weigh the same as the next quarry's #57 stone.

When you hand us scale tickets, we can also calibrate density empirically: if your loaded weights consistently come in higher or lower than the density assumption, we surface that drift back to you so you can update the density value for future flights.

The flight tells us what's physically on the ground. Your scale tickets tell us what you've sold and what's been delivered. Reconciliation is the comparison between the two — and the gap is where your money lives.

You drag and drop your scale ticket exports into the dashboard (or we pull them from your scale software directly). The platform reconciles them against the measured inventory and surfaces drift in either direction: over-scaled means inventory shortfall (you've sold more than you actually had), under-scaled means phantom inventory (your books say more than the drone can find). Either way, you see the gap in dollars, by material, in the month it shows up — not at year-end.

Here's the most important thing to understand about what we sell: most aggregate yards never physically measure their inventory. They trust scale tickets, watch the piles, and reconcile at year-end. The 3-5% drift that quietly accumulates every quarter is the result.

We give you a physical, independent measurement of every pile in your yard. Month-over-month change detection — what reconciliation actually depends on — is typically tighter than 1.5% on undisturbed piles; the absolute volume against survey-grade ground truth lands within 2-3%. That's not perfect. But it doesn't need to be. The drift is bigger than the measurement error, which is exactly why the drift is detectable. Verification beats estimation, even imperfect verification.