From Two-Hour Waits to Real-Time Flow: Building Smarter Grain Logistics
- May 6
- 3 min read
By Bryan Wattie
Founder of GrainFlow
I didn’t grow up thinking I’d build software for grain logistics, but I did grow up around agriculture, working across Canada and seeing firsthand how complex and operationally intense the system really is. What surprised me most wasn’t the scale. It was the inefficiency hiding in plain sight.
The moment that changed everything came from a simple Facebook post.
A friend of mine arrived at a grain elevator at 9:55 a.m. for a 10:00 a.m. delivery. He was hauling about $30,000 worth of canola. When he got there, there were 17 trucks ahead of him. He waited two hours. The frustrating part? He lived 10 minutes away. If he had known what the line looked like, he would have made a completely different decision.
That moment stuck with me. I thought, I can look at that line and estimate wait time. Why can’t technology do the same?
That question became the foundation of GrainFlow.
GrainFlow is a yard intelligence and smart scheduling platform designed to help grain elevators reduce congestion, improve throughput, and ultimately build stronger relationships with the farmers they serve. At its simplest level, our system uses video analytics on existing security cameras to count trucks in line and estimate wait times in real time. That data can then be surfaced wherever it’s needed, inside an app, on a dashboard, or directly to farmers making delivery decisions.
What sounds simple unlocks something much bigger. It creates visibility.
Today, grain logistics often operate with limited real-time information. Farmers make decisions based on habit or guesswork, and elevators rely on manual scheduling processes that can take weeks of back and forth phone calls. The result is congestion, inefficiency, and frustration on both sides.
With better data, we can change that. We can move from reactive decision making to proactive coordination.
But building in agriculture comes with its own realities.
It is a relationship driven, risk aware industry, and adoption takes time. Our first customer came through cold outreach. The problem resonated immediately, but it still took months to close the deal. From first conversation in September to installation the following May, it has effectively been a year long journey to get the system live.
That pace can be challenging, but it also reinforces something important. When solutions truly align with real operational pain points, they stick.
What keeps me motivated is the potential for network effects. Every grain elevator serves hundreds of farmers. Every farmer interacts with multiple elevators. As we expand, each new connection strengthens the system, creating a shared layer of visibility across the supply chain.
Looking ahead, our vision goes beyond counting trucks.
We are building toward a fully intelligent, context aware scheduling system. One that can take weeks of manual coordination and reduce it to a few clicks. A system that understands constraints, adapts in real time, and helps ensure that most deliveries happen within a predictable window, ideally under 30 minutes.
At scale, this becomes more than efficiency. It becomes trust.
When farmers can see what is happening before they arrive, and elevators can manage flow with confidence, the entire system starts to work more like a well oiled machine. Even small improvements in coordination can unlock meaningful time savings across the industry.
For me, this journey has been about taking something that everyone accepted as just the way it is and asking whether it has to be.
Because sometimes, the biggest opportunities are not in creating something entirely new. They are in finally making the invisible visible.
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