The $3B Company Trying to Beat Amazon Prime

Molly O'Shea (0:00)

Welcome to Sourcery.

Sean Henry (0:10)

The potential of photonics.

Molly O'Shea (0:12)

The technology to interconnect these GPUs. Global payroll and HR platform.

Sean Henry (0:16)

8 billion operational data points.

Molly O'Shea (0:18)

Scale-ups over startups.

Sean Henry (0:20)

You'd rather have a million of something than one of anything. Building the intelligence layer through the fence. There isn't enough power, there's not enough memory chips.

Molly O'Shea (0:27)

We're at the end of physics of what we can still do.

Sean, welcome to Sourcery and Strike. We're out here in Monaco. Technically, Cap Ferrat, but we'll just go with that. How are you doing?

Sean Henry (0:50)

Doing great. It all blends together to me as well. But it's incredible to be here. What a beautiful venue and thanks for having me on the show.

Molly O'Shea (0:56)

So you're the founder of Stord. People who don't know what Stord is, could you give us a little background?

Sean Henry (1:01)

Yeah, so Stord really exists to level the playing field with Amazon Prime for the other two-thirds of commerce on the Internet. When we look out there, we think that Amazon's product really is delivery. And that's what all other merchants struggle to achieve. And it's what keeps all of us as consumers going to their website to check out instead of independent merchants. So we really see ourselves as the physical intelligence layer combining all the fulfillment and delivery, all of the commerce software, and all of the applied robotics and AI to achieve Amazon level delivery costs, speeds, and consumer experiences.

Molly O'Shea (1:37)

And so for people that aren't aware, you recently had a milestone of funding and growth. Where are we at with the business?

Sean Henry (1:44)

Absolutely. So earlier this year, we announced a $250 million Series F. That was really to not only continue scaling the business rapidly, where this year we'll be crossing a billion in annual revenue.

And over the last four years alone, we've 10x the business in terms of scale and revenue and both volume. And so it's a lot of fueling that future growth, where there's so much of an advantage of scale. Scale drives economics. It also drives density. And that's really what builds the moat in delivery, enabling Amazon level speeds and costs. So continuing to press on the gas hard with scale. We also announced Stored Labs along with it, which is very much an application of all of the latest robotics, AI, drones, but also a data foundry actually training the robotics in reverse. And so we're really excited about how really all the new technology is enabling a vertically integrated industrial business like us to just keep separating our moat from the existing industry we live in.

Molly O'Shea (2:41)

Let's get into that because robotics is super hot right now. It's flying. It's like become the age of robotics. Why is now the time to go hard on that?

Sean Henry (2:51)

Yeah, if you really look back over history, a lot of the problem with robotics is kind of the dumb robots, where if anything goes wrong, if any variable is changed, they can't succeed in that environment anymore. So if you have a operationally complex environment where every minute or hour could be hundreds of thousands of dollars or more of productivity, that traditional robotic operation can be quite risky. So now you're getting to this point of agentic robotics where you're having robotics that are building real world models that can see videos for very brief times and learn how to self-heal and get back on track. So let's say you get a slightly different size or form factor in a unit in a fulfillment center. Does all of a sudden that go down until IT can show up and code or do something different? Or does the robot learn on the fly with one worker walking up and holding it for three seconds and showing them how to put it in the box? And so that's really where robotics is going and why now is such a moment for it. Yet at the same time, if you look back through history and if you study kind of the Teslas and SpaceXes of the world, the whole process and equation is how do you go from refining your processes physically and operationally to then software and kind of repeat that loop over and over again? And only then can you really get the advancement you want in hardware because now you're applying it and really hard coding, whatever that process was. So if it was under optimized, you're going to fall behind now in a hard coded way. That's really the issue with robotics in today's world because a lot of the physical world out there that needs these robots doesn't have the basis of that best-in-class process or vertically integrated software to go apply the robot. And so that's kind of the chasm that robotics is going to have to cross in the period ahead now that they are getting more agentic and self-healing as well.