Why We Started Oway

A factory is a stream of decisions

A factory makes decisions all day. Which supplier ships first. Which line runs which order. Whether the part in one building is the part a team three states away has been waiting on since Tuesday. Whether a truck can take one more pallet today, or whether that pallet waits until Thursday.

Every one of those decisions depended on information that lived somewhere else. The ERP knew what we ordered. The floor knew what we built. Suppliers knew what they shipped, carriers knew where their trucks were, and none of those systems could see each other. So people carried the information between them, by phone, by email and in spreadsheets that only one person fully understood.

We were good at it. We grew because our people coordinated faster than our competitors did. But I always knew what we were paying for that speed: buffer inventory, idle lines, half-full trucks and engineers spending their afternoons chasing status updates.

Every operator pays the same tax

When I compared notes with other operators, I heard the same story in every industry. Different products, identical blind spots. Every company had spent heavily on machines and software. Almost none had a way for those systems to share what they knew with each other, or with partners, in real time and on their own terms.

The cost is large. Moving goods through the US economy cost $2.6 trillion in 2024, about 8.7% of GDP.¹ A meaningful share of that pays for coordination failures: trucks driving empty, trucks driving half full, freight waiting in terminals and inventory parked as insurance against not knowing.

For a long time there was a good reason nobody fixed it. Coordination depends on context, and context is messy: an EDI message from a system built in the 1980s, a PDF purchase order, an email that says "can we push to Thursday," a driver running late because a dock in Ohio is backed up. Software could store that context. It could never read it.

That changed. AI can now read the messy, real-world context coordination depends on and act on it inside clear limits. We founded Oway in 2023 to work on problems that simply were not solvable before.

Why trucks first

We needed a first problem where the waste was enormous, the data existed and the result could be counted to the dollar. American freight checked all three boxes.

One in every six miles a US truck drives is driven completely empty, and the average loaded truck carries a third to half of what it is rated to haul.² A few miles away from that empty space, a shipper is paying premium LTL rates to send six pallets through a chain of terminals where they will be unloaded, sorted and reloaded. The capacity and the demand are often on the same highway, at the same time, going the same direction. They cannot see each other.

So we built the thing that lets them. Oway OS lets a shipper move 1 to 18 pallets in space a truck is already carrying, at up to 50% below market. Carriers earn more on routes they already drive. Juno, our industrial AI, prices and books each move in seconds. Today more than 10,000 vehicles are on the Oway network.

Where this goes

Trucks are the first surface. The same pattern shows up across industry: production lines, warehouses, robots and energy. Capacity that exists, demand that exists, and no shared, trusted way to match the two. That is why we are building IOI, the Internet of Industrials, so the systems the physical economy already runs on, and the autonomous machines arriving now, can share what they know and act on it together, with permission.

This series is the story of what we learned along the way: what America's half-empty trucks cost, how China raised its own load factors with freight matching, how a regulation and a pandemic gave America the beginnings of a physical context layer, and what it takes to make the physical economy legible to software and AI.

If that sounds like work you want to do, come build it with us.