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Live from GTC: Unlocking Hidden Revenue in Retail with Whale's Chris May
00:06:21
Live from GTC, Chris May, US Country Head of Whale, breaks down how their vision-language AI is transforming retail operations by turning everyday camera footage into real-time revenue insights.
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Foreign.
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Welcome to reshaping workflows with Dell Pro Precision and Nvidia, where innovation meets real world impact in high performance computing.
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Logan, live from GTC 2026. And I'm actually sitting down for an interview, which is fantastic because I have not sat down for one in a while. So I'm here with Craig Chris, also known as Jerry from Whale. So Chris, let's get started. Tell us a little bit about you, your role at Whale and what Whale does.
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Sure. Happy to be here. My name's Chris. I'm the VP of Sales country credit for Whale. We've been around for about eight years. This is year number one for the US expansion. What we do is basically AI for store operations and revenue growth.
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Store. So store operations for revenue growth. Define what that means.
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Essentially we focus on how to ultimately increase revenue for any retail settings. Right? So think revenue leaders are interested in things like how many people walked in the store, how much time are people spending in certain location in the store? Are we losing money because people are leaving because they're spending too much time in line or for auditing purposes, Right. Like are people making burritos or coffee the way that they're supposed to be making? Are people wasting food? So those type of things we could do with our devices and what we call a VLM visual language model, vision language models on the back end that does all the, all the smart work, computing back end and essentially gives revenue leaders these type of numbers and analytics so they can make better decisions.
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Got a follow up question. So pretty familiar with, you know, VLMs, right? So let's say we take this little camera, we'll use a grocery store example, right? And let's say people are loitering too long in the beer section because you know, they want beer, whatever it is. Right. So tell me a little bit. How does Whale. Is Whale fine tuning this model? Like what additional context are you buying of something that's off the shelf that then. And then where does that go? Where do you kind of fit in? Like the, I'm not going to say revenue pipeline, right? But where do you fit in kind of that, that context chain of the information that you're collecting, where does it fit in? Like the ERP or whatever systems that they're using within a grocery store?
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Yeah, that's a great question. So in the example that you've given, right, like different revenue leaders have different KPIs and different things that they really care about. So one of the customers that we work with is LVMH and Obviously the things that they sell are more, more high end. They're selling, you know, 20, $30,000 products. Right. So what they may essentially care about are things like are my product displayed correctly or you know, are there people that I'm that are not intended to. Right, the people, potential buyers, Right. So a big vertical is also for us is automotive. Right. So if I walk into a car dealership and I'm walking around the car for very long, right. Why, why am I not being attended to? I'm a potential buyer that, you know, could lifetime customer, lifetime customer value could be about half a million dollars. Right. So these are the things that revenue leaders that manage essentially 2,000 stores, they really care about. So how many people or what's the time that people are not attended to across 2,000 stores? In the case that you mentioned, safety and security, loss prevention is also a big thing, Right. Like we can do dwell time analysis. So if somebody is spending a lot of time around an area where typically if you're picking up beer should probably be no more than 30 seconds, but we could create an alert where if somebody's at a section for more than a certain amount of time, we probably want to have a set of eyes on this person. And so it's really different for different environments. But the beauty about VLM is you can prompt it to do visual search and the models are already pretty, pretty good, right. CV's been around for more than a decade now. So things like, you know, I don't want to say facial recognition, but we could do people tracking, dual time analysis, demographic information. Those type of models are out of the box, ready to go. But it's also very easy to custom build some models with data available. Typically with any store that has some type of CCTV setup, it's pretty easy to configure that.
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And last question. So I mean lvmh, we're talking Louis. For those that don't, those that don't know, we're talking Louis Vuitton and more than that obviously. But like for example, are, are you selling kind of the software, like you know, the software layer, do you also sell kind of the, you know, I'm not going to call this an edge device, but it is an edge device like the camera. Can you integrate with other systems that are already in place? Kind of. Tell me a little bit about that.
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Yeah, so I think what's, you know, we kind of are out of the SaaS world. It's more of the past world now platform as a service. So for us, you know, there's multiple ways to work with us. You could just have the software where you just want to analyze some footages. That's fine. But in retail locations, typically most stores have their CCTV set up. So we have these AI boxes. They're just doing computing on the edge, Right. So it's very easy to plug this into your current CCTV system. It does the computing on the edge. The footage never leaves the store and the data gets up. Just the data portion gets uploaded. And then we do analytics on the cloud. So you could see a dashboard there. But if you want a smart camera or if you want a smart recording badge, we also provide that as well.
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All right, Chris, Jerry, if someone's interested in learning more about whale, like, you know, tell us website socials. Where can we find you?
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Yeah, so you can find me, Chris May on LinkedIn. Our website is actually Meatwell AI. So m e t w e AI. I think somebody took the whale AI domain. So, yeah, find us on Meatwell AI.
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I love it. So check them out. Was it meat? M E E T. But you know, a whale is meat, right?
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Be pretty funny.
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It would be actually funnier if we did that. But anyways, gomeatwhale AI. Check it out. Logan from gtc. I'll see you on the next one.
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