Inside Stord: The AI & Robotics Shipping 100 Million Packages

0:00 The reality is often these antiquated industries need a fresh perspective. They need someone to come in who's a little bit naive, a little bit overly optimistic, and just start working against the problem. >> Hi, my name is Simone Melby with Forbes. I'm here with Jacob Boudreau, CTO and co-founder of Stord. Thanks for being here, Jacob. >> Of course, thanks for having me. >> Let's start off by explaining what Stord is for an average consumer. >> Sure.

0:27 So, anytime you buy something online, there's a huge orchestration of effort that goes in behind the scenes. Stord is that physical intelligence layer for brands. So, we bring all of the hardware, the software, the physical logistics, and the infrastructure together to take that purchase through its delivery to that doorstep. So, we're really bringing prime-like and Amazon-like capabilities for everyone else to the end consumer. >> Can you tell me about your experience working and what you were doing before you started Stord?

0:57 >> Yeah, so prior to Stord, I'd started a few small businesses online, and that really morphed into software development into a software agency that I grew and scaled and built all sorts of different applications for startups, but also leading international pharmaceutical companies, and ultimately transitioned into Stord with a focus on building a product that compounds over time. And one of the things that I think is exciting about Stord is we touch a lot of different service areas. So, it's not just one challenge, it's 100 different challenges that each grows with scale that we get to solve.

1:28 >> What technological problem were you trying to solve with Stord, and how does Stord software compare to other logistics companies or ordering companies and warehousing companies that handle those sorts of things for other brands? >> When we set out to build Stord, one of our core theses was that the software and the physical infrastructure have to be built together. So, step one, we built this tight feedback loop between everything that happens in the operations, whether on the floor, whether out for delivery, and the software itself. So, what that looks like for us is an entirely vertically integrated tech stack. So, we've built all of our software that runs the buildings, that runs the routing, the parcel decisions, the actual software that the brands live in and operate their business, as well as all the way through interactions with the consumer.

2:15 So, the delivery promise, the ship options, the tracking, the returns, the subscriptions, you know, you kind of you name it. There's a wide array of products at this point. And I think one of the things that's exciting for us is because we've built this feedback loop between the physical infrastructure and the software, we also have this robust data business that we call it our data foundry where we're ultimately capturing a number of data points, whether footage, whether systemic, that are feeding into various models and systems as well as we train AI both in our business, but also externally.

2:46 >> What was the process of building up the software in the sense that who did you bring on? what kind of trial and error was there? That sort of thing. >> It's been a long journey in our software, no doubt. you know, we're we're 10 years into the business and we've built a number of products since then. and I'd say at the start, we faced this iteration back and forth where we wanted to ensure that we solved our customers' challenges. And I think one of the things that a lot of founders struggle with is how far do you go from an ambition standpoint right at the beginning versus a practicality standpoint because you don't want to over-engineer, but at the same time, you need to prepare for the future. I think one of the things that we learned along the way as we built out our engineering team, as we built out some of our products, was that we needed to engineer further ahead for the future.

3:32 So, early on, we we had to do a few different rewrites or expansions of the product, but since then, we've built on a foundation that's scalable. And so, you know, I'm proud to say that we've 10xed our volume, you know, many years over, and we're still able to support it on our systems. And I think a lot of that comes down to bringing on the right people, bringing on the right talent. And so we've got a phenomenal team of world-class engineers, product managers, AI engineers, forward deployed engineers, and it's been awesome to get to work with them.

4:03 >> Say I'm one of your clients like Athletic Greens or Native, what do I look at whenever I'm like looking at my computer and what software and what user interface am I interacting with when I am partnering with Stord? >> If you're one of Stord's customers, you're logging into Stord's order management system or perhaps you're even interacting through Claude or OpenAI through Stord's MCP and you're just chatting away with your data. But ultimately, you're logging into Stord's OMS and from there you're getting a full single pane of glass of your entire business and operations. So everything from all of your purchase orders outstanding, your sales orders, all of your inventory across your network, how that's varying across your consumers so you understand your consumer behavior, what that looks like from a demand forecast, and ultimately all of the tools that we've built to help these brands, whether proactive, whether AI recommendations or an AI-driven chat, they're all embedded throughout that experience so that a brand can just log in, immediately understand what's going on with their business, and then action on any steps that they need to take.

5:04 >> Why has the warehousing business or industry been antiquated for quite some time now? What was preventing them from upping their software and becoming more advanced? >> I think it's been an interesting question to grapple with of why hasn't this been solved and why is there so much of this kind of antiquated feel to the industry? And I think there's a few different trends that carry into it. So one is there's been a rise in consumer expectations. I think, you know, we we all definitely know that one. We've definitely seen it with Amazon pushing the boundaries, but also even in the gig economy and you've got the DoorDashes of the world that are getting your food in 30 minutes or less. And so consumer expectations have dramatically risen.

5:47 Additionally, I think some of the technologies underpinning this have become widely more available in the past 20 years. So, historically to run high volume, high scale fulfillment operation, you didn't necessarily have cloud access 20 years ago. So, it didn't make sense to build cloud software that was also scalable across public facilities, which are these facilities that operate in multiple with multiple tenants, multiple brands in them. So, it just didn't make sense from a business model perspective.

6:14 And then additionally, I think with the form factors, the commoditization of hardware, the cloud availability, the rapid developments particularly in AI as well for code gen, it's just become much more feasible for company like Stord to exist where we've really then brought the technology that needs to exist in the network and in the the market straight into the physical infrastructure. And so, when we've created that feedback loop, I think it's created this ability for us to act faster and and push the boundaries on the consumer expectations, which just hasn't historically been tightly woven together because typically what's happened is someone's opened a facility because they know how to run the operations, someone's built the software because they know how to build the software, but they haven't ever brought them hand in hand together to build them purpose-built for brands.

7:01 >> What are some of the factors that make Stord operationally efficient? >> Man, we could go down a long laundry list of factors here. A couple of the things that I would say stand out. So, first and foremost, we are we have a vertically integrated tech stack. So, that means when the order comes in from the shopping cart or maybe even before that when we're providing the estimated delivery date through the ship options, that data is immediately running into our order management system. We're making the right routing decisions, we're placing it in the right facility. So, even before it shows up in a building, we've identified where is their inventory, where does demand sit, what's the most optimal parcel and shipping cost to place it in the right location. Then once it gets there, it runs into our warehouse management system, which is also vertically integrated into our OMS. And so, it automatically starts to batch and route these orders to the relevant location in the building, as well as based off the right threshold, based off SLAs and carrier pool times. And so, even before somebody touches a box or picks, you know, picks an item out of a bin, the system's already made a number of key decisions. And along the way, you know, we've have a variety of different methods to solve for this, whether algorithmic, a rules engine, ML models, and more, that are helping to ensure the right decisions are made along the way. And then when you get into our buildings themselves, like we're in right here, you can see it in the layout of the the floor. So, we do a lot of intelligent slotting and pick path optimization. So, you could think about a picker or a packer knowing exactly where to go in the building in the minimum number of steps to ultimately drive efficiency through the building and and drive the highest number of orders. But, it shows up in all those little pieces, which I I think is the exciting part about what we get to work on, which is AI, ML models, algorithms, and more are applicable at a broad scale, but they're just as applicable at all those little 1% improvements that add up cumulatively to drive a differentiated experience for our brands and ultimately for consumers.

8:56 >> How does Stored get more efficient as the company scales? >> Yeah, one of the things that I I think has been really exhilarating for me as we've built Stored over the past decade now, is that we have gotten significantly more efficient, significantly faster, and driven better outcomes as we've scaled. And that's usually counterintuitive cuz, you know, most people think like as a company scales, you get all these layers of, you know, bureaucracy or you start to slow down.

9:22 And it's been the complete opposite with Stored. And part of that is because we drive a ton of ownership into every aspect of our business, and that comes with deep technical integration so that every single team member can see what's going on. They have the visibility at every level in stack on the business. But then additionally, as we scale, we get the ability to invest in that next level of capabilities that may only drive the 1% improvement, but 1% on 100 million orders is a is a big improvement. And so we just tackle every single one of those problems day by day. And those cumulatively add up. And then I think additionally, one of the things that we're excited about is we've recently launched Stord Labs, which is I'd call it an epicenter of a lot of our innovation, our robotics, our AI efforts and more, where we're not just applying those 1% improvements. We're actually looking at step changes as well.

10:15 So we're partnering with leading robotics labs. We're taking data from our our business and using it to train new models. And so I think with that, one of the things that we found is as you scale, you just get more opportunity to tackle that surface area of the problems that you know can be improved and can be optimized. >> So far you've expanded internationally into Canada and the UK, to name a few, with plans into Hong Kong.

10:42 And can you talk a little bit about what challenges come with international expanding? >> It's a fun challenge to expand into new markets. of course, there's a lot of things that are similar. You know, you still have to run your business. You still have to understand the numbers. You still have to ultimately balance out your costs and your investments. but I think one of the interesting and fun parts about it is you get to learn the specific dynamics dynamics to that market. So whether that be consumer expectations that differ on delivery speeds, whether that be where the optimal positioning for facilities are, or just the best talent to bring on board. I think the fun part and challenging part is every market is just a little bit unique. So learning those nuances and then ultimately building the business model around it, so that you don't just, you know, copy and paste what you've built elsewhere, but you ultimately mold it specifically to that market.

11:34 >> What's your long-term hope for implementing robotics into warehouse warehouses? >> Yeah, I think one of the exciting parts in our business, given that it's a very industrial, very intensive business, is that I think robots can help every single individual across stores operations be more effective and also be safer. You know, at any given time we practice a ton of safety regulations or requirements because we want to ensure that when you're picking heavy packages or you're moving a forklift around, that everyone's accounted for and everyone's safe. And this is an area I think robotics shine. When we think about the ability to detect, you know, a person around corners, around aisles, when we think about the ability to lift heavy weights, there's a ton of leverage that I think robotics can apply. And then ultimately, I I do think that one of the large areas that is most critical for brands and also ultimately for consumers is can it drive faster throughput and faster delivery. And this is something that we've applied automation both sort centers, but also robotic arms and more, where you take some of these repetitive tasks or steps that allow a package to move into a courier, into a delivery van, and you just rapidly flow through those to get a faster delivery so that the consumer can, you know, shop online and immediately get the, you know, your order's been shipped and arrive same day or next day.

12:59 >> How has your role at Stord changed as the company has grown? >> Yeah, roles as a founder change a lot as your company grows and I think one of the pieces there has been shifting from you know, maybe being directly hands-on. I still remember the days where I'd ship code to production. Those days are, you know, I I still mess with it now and then, but those are largely behind me. So you shift into more of this management cadence where you get to see outcomes through your broader team and that's been an exciting step. But, I think also one of the things that has been fun over the past 10 years in that shift is a lot of people may think, you know, you're doing warehousing, shipping, delivery. It's got to be very operationally intensive, but it's it's also very technologically intensive. And so, seeing the ability to really morph and shape our operations from a technology lens has been an exciting step in that. And so, what I enjoy about how my role's shifted over the course of Stord is I get to work with some incredible operators, some incredible leaders. And we have this fun feedback loop of, you know, what's the the leading edge of technology that we should be embedding in our operations? And do we need to think about it from a first principles perspective? Rather than take what's worked historically and apply technology to it, should we rethink it completely?

14:17 And that's been a really fun transition over that time. >> Moving back to Stord Labs, what do you anticipate for that venture in the future? >> We're We're really bringing it together as kind of the epicenter of some of these step-level changes in our business, both from applications of robotics, applications of AI, optimizations within our operations, and more. And so, when I think about Stord Labs, I think about it in a few lenses. One is just an operational improvement engine.

14:47 So, taking the best of both external robotics vendors, external, you know, frontier lab AI models, or internally built, you know, kind of taking commoditized hardware, applying our software to it, and deploying it in operations to one drive operational improvement. But, there's a whole second side of Stord Labs, which is taking the data, taking the operations that we have in our business, and using those to partner with robotics or AI labs to help them train their world models, or, you know, train the dexterity of their robots. So, it's a really interesting feedback loop. And when I think about the long term of it, I would expect to see some pretty material step change improvements and changes in Stord's operations, both from an automation and robotics perspective, but even just in day-to-day, you know, manual steps. And then I would expect to see a number of new ventures spin out of Stord Labs as we continue to take that feedback loop of Stord's operations that are at scale now, you know, nearly 5,000 associates, 100 million packages a year, cross, you know, internationally, taking that scale and using it to feed into new models or new businesses.

15:53 >> What advice would you give to entrepreneurs looking to innovate in an antiquated industry? >> The short of it is just get started. it's very easy to look at an antiquated industry, to see a group of people that, you know, are experts, they've been doing it for 40 years or whatever it is, and feel like maybe you can't break in or maybe you can't solve this massive problem. And I think at the end of the day, the reality is often these antiquated industries need a fresh perspective. They need someone to come in who's a little bit naive, a little bit overly optimistic, and just start working against the problem.

16:30 Apply, you know, their expertise, apply their technology, their systems, their knowledge, their approach to the problem, and ultimately, you know, just iterate from there to get the feedback and grow the business. >> Thanks so much for chatting, Jacob. This is really appreciated. >> Yeah, likewise. Thank you for having me. It was great to chat.