Tony Safoian [00:02:06] Please welcome a customer from one of our favorite – we love Canadian customers, love our office and our people there, and I would venture to say that Daisy Intelligence was one of our first big customers and – have Gary Saarenvirta here today, founder and CEO of Daisy Intelligence. Welcome to Cloud N Clear.
Gary Saarenvirta [00:02:31] Great. Thanks very much, Tony. Look forward to chatting with you.
Tony Safoian [00:02:34] Likewise. No, legitimately. This was one of the first meaningful relationships we had up there when we became your partner. I think literally – two people, maybe three in all of Canada. And now we’re like, you know, 45 or so. It turns out that it’s not only a great local market, but it’s a great pool of talent to serve all of North America. So we have very heavy investment in engineering and in other functions. And we’re super excited. So thanks for being on. I don’t get to talk to our Canadian customers like this. So thanks for being on Cloud N Clear.
Gary Saarenvirta [00:03:09] Oh happy to be here and excited to be part of this and to share our story or, you know, and then have a nice chat today.
Tony Safoian [00:03:16] For sure. For sure. We were just sort of talking about before we pressed record, you know, 20-year founder, CEO, your 18-year founder, CEO, pretty rare these days. Seems like based on what we’re talking about, you’re still very active, hands-on, meeting customers, all the stuff that I think builders like you and I love to do. But tell us about even before Daisy Intelligence, how did you get into the space and what got you to launch the company? How the company’s – you’ve been in the game for a long time.
Gary Saarenvirta [00:03:48] Yeah, I mean, so I have a technical background. I have a master’s degree in aerospace engineering. So and, from the University of Toronto, which is, you know, a great school, which is a why there’s a lot of great tech talent here. One of the reasons. But yeah. And then, you know, so big background in math and science and not much of an aerospace industry in Canada and, you know, wasn’t ready to leave Canada at the time. And so I kind of backed into working with large corporations. And I was really shocked at how little math and science big companies used to make operating decisions. And so I kind of created this accidental career of bringing more math and science to business, always with a bent to, you know, to deliver financial results and outcomes. And so after grad school, I worked with a company called LoyaltyOne that runs the Air Miles Reward Program, a large coalition loyalty program. And they have a lot of retail customers and grocers. And they got exposed to retail data and became one of the first worldwide users of IBM’s technology. Data mining was a buzzword back in the 90s for AI, you know, it was like data mining. I think the terminologies changed more than the technology has. And, you know, really got into playing with huge volumes of data using machine learning technology back in the day. And then I ran IBM Canada’s data mining practice and their data warehousing practice and was kind of one of their, you know, global go-to people for high-end analytics work. And along the way, I kind of realized that machine learning in its current form, what everyone thinks about today doesn’t quite work for complex problems. And I think the world is living through the experience that I lived through 25 years ago, just by accident. And I was super excited. Predictive analytics can solve everything, you know, and I realize that it’s not quite enough. And so I thought that, you know, IBM is a great business, you know, great company. You know, I’d say they’re good at everything, masters of nothing, maybe? If it was not too unfair of a commentary. And I thought I could take my analytic skills and my math skills and, you know, my goal was to help companies operate smarter. And I thought this AI should be autonomous, you know? That’s a key defining feature. And so we built some autonomous technology and bringing my aerospace roots so that, you know, you see.
Tony Safoian [00:06:02] What do you mean by autonomous? Let’s educate the listeners.
Gary Saarenvirta [00:06:05] Yeah, autonomous means a system that works with no human in the loop. Does thinking for itself, makes decisions. Could be a very narrow scope. Like you know, it’s not, you know, our technology doesn’t make you a cup of tea, but it can solve its specific problem. I would say, like the ingenuity helicopter that just flew, it flew by itself. It’s got a set of software and logic and there’s no human in the loop. And I think, I kind of brought some of my aerospace thinking when I kind of realized that predictive modeling or supervised learning doesn’t really do the problem on its own. I went back and look what the aerospace has been doing for 50 years, which is, you know, military fighter jets have an element to fly by wire that the pilot doesn’t actually fly the plane. And certainly NASA kind of, you know, kind of rovers that are out there are autonomous systems, right? And so the idea of taking autonomous logic with the science first, all those systems have the laws of physics in it. And it’s not a data learned laws. It’s like the theory, human-led theory. And so we took that approach and we created kind of theories of business first and then get the data second. And I think that’s been a unique kind of differentiator in our approach. And as far as I know, we’re one of the very few, if not the only one outside of the engineering and science domains that’s taken that kind of scientific method and part of the business and our vision is the autonomous enterprise, right? And, you know, we believe in a future where computing machines improve our lives, and that means making companies more profitable. That means it will lower the cost of living for you and me, because if we make smart companies reinvest in price and innovation, which ultimately impacts the consumer, and then ultimately we want to make human beings’ jobs easier. And I read a survey that said the, you know, the fifth most important reason you take a job is because you love the job. That’s pretty sad. It should be the number one reason, right? So if we can take away some of the drudgery, let computers do the gory details and computing and repetitive high volume activity and let people do what people are good at, right? And there’s a place for both. I don’t advocate replacing humanity, but, you know, that’s kind of what Daisy does. That’s our vision.
Tony Safoian [00:08:17] Totally, totally. I think the human factor will always be there in terms of the creative arts, you know, things like, of that nature that I think humans excel at. At least for now, you know, singularity may change that sometime – So much of business process and decision making with all this tool sets being available, I think in a more democratized fashion than ever before, more affordable than ever before, it’s still like just very, very early stages of how much of decision making gets automated.
Gary Saarenvirta [00:08:53] Yeah.
Tony Safoian [00:08:53] So Daisy Intelligence was formed, it seems then out of your IBM experience, but also maybe the limitations you felt of what you could do there.
Gary Saarenvirta [00:09:05] Yeah, and I thought I could do it better, faster. I founded the company, I thought fraud detection was the killer app. I thought, you know, who is committing fraud against large corporations? It wasn’t just the individuals. It was like, I think organized activity, organized crime and terrorism. And I thought, you know, we can help lower the cost of insurance, but we could also stem the funding for some of these nefarious activities. And I thought that fraud was the killer app. And we started building like a fraud detection solution. So kind of autonomously identifying, you know, insurance fraud and then quickly go to bank fraud. And, you know, but, you know, the world doesn’t move as quickly as you kind of want to. And so we’re still I think, you know, kind of in the early 2000s when we were doing this, we did a lot of pilots and work with big insurance companies, but they weren’t ready to take it and really deploy it. So I think we’ve been ahead of the curve all along the way. And, you know, that’s a challenge when you’re trying to grow a business to be disruptive and kind of a bit different. So around 2008,9, the big financial crisis and the kind of interest in fraud kind of ended for a while there. And then we picked up in retail doing a lot of work in retail, around merchandise planning. So helping retailers decide what to promote, what prices to charge, how much inventory to allocate. And again, our systems deliver the answer. You know, even on the insurance side, it’s like there’s no human required. There’s no data scientist on the client’s side. We could just plug into the backend system and say, pay this claim, don’t pay this claim, or you should charge this price. Put 100 units of coke in that store, put some in the distribution center. You know, it’s that kind of vision of autonomous. But that doesn’t mean you replace a person still, because the human’s still the boss, human sets the strategy and the objectives. The AI takes care of the details, right?
Tony Safoian [00:10:52] Yeah, for sure. I mean, that pivot that you described, probably one of many, I think. Anybody who’s been around in tech service – 20 years or so has probably pivoted a bunch of times in at least the successful ones, right? Like you have to read the market, you have to read the -Customers often take you in certain directions if you’re receptive and paying attention. So that’s one sort of big pivot you describe. What are some of the other memorable pivots going from fraud detection to retail, but other pivots, whether they were strategic or geographical, what sticks out in the story of Daisy Intelligence?
Gary Saarenvirta [00:11:31] Yeah, I think I mean, we started out doing professional services. And so I had the, you know, IBM had this great mentality of, you know, they call it first of a kind development. So when you do development, you need to develop with a customer. The company’s not going to fund product development unless there’s a customer in the mix. And so I thought, OK, we’re going to do professional services with a view to build some software. And so we did that with customers. We worked with a few customers at a time and I kind of self-funded the development of the technology. So at that time we had no outside funding. It was just the way that we ran above 30 million in revenue through the business over a decade. And we took hundred percent of the profits of that, and I poured it into software development. And so then the big pivot was, you know, when we started to get investors is like, OK we got to throw away I’ll do work for anybody, for anything, you know, that’s in our domain of capability. Right? And then say, OK, I’m going to focus on this product and I’m going to just do that. I’m going to say no to all these requests for services. And that was a massive pivot. And I’d say kind of in –
Tony Safoian [00:12:32] Isn’t it hard? Isn’t that pivot really hard? Just – thing that you used to do and now don’t want to do. Such a –
Gary Saarenvirta [00:12:40] That’s brutal. Still I mean, you know, as an entrepreneur, I still struggle with that. Which is like, yeah, oh I can do that. We can do that. We can do that. We can, you know it’s like –
Tony Safoian [00:12:48] That’s the other pressure is like this promo about, you know, crypto and – other automation, like just all the stuff that’s like always kind of there, and we have this role as leaders to have our finger on the pulse of what’s going on so we don’t miss the transformational relevant things.
Gary Saarenvirta [00:13:09] Yeah.
Tony Safoian [00:13:10] But you have to really deliberately try to ignore everything else. It’s really hard.
Gary Saarenvirta [00:13:14] Absolutely. Yeah it’s very difficult. And so that was a big pivot going professional services and going from non-recurring, 100 percent non-recurring revenue to 100 percent recurring revenue. And we kind of did that in 2015, 16. I felt our technology was ready for prime time. We had built it with customers over a decade. We had tested it, proved that it worked. And so not being savvy in the investment game, I think I kind of de-risk some technology. And, you know, we kind of undervalued what that was worth initially. And we kind of were treated like a brand new startup, even though I had written like tens of millions of lines of code that we had spent 10 million dollars of company profits building. And so that was just kind of not knowing. And, you know, my family didn’t come from big business. You know, my dad was an auto mechanic and owned his own business. And my mother was a hairdresser and owned her own business. Yeah they were business people, but they weren’t in from this kind of savvy investment world, right? Yeah. Yeah.
Tony Safoian [00:14:10] So what happened after that? You raised capital?
Gary Saarenvirta [00:14:13] Yeah, we raised capital. And then we really started to, you know, focus on growth. And, you know, we went from one customer to 15 customers over the last five years. We kind of tripled, tripled, doubled in revenue, then the pandemic happened. You know, we’ve raised like 20 million dollars and kind of, we did some seed capital rounds like five million and then raised like 15 million into kind of in a series A extension. And we’ve kind of grown from customers in Canada to kind of 50 percent of our businesses in the US. US retail focused on grocery, high-frequency retail, grocery, drugstore, hypermarkets. And we got one grocery customer in Europe and insurance customers in Canada, some international brands of multinational brands and channel partners now in about seven geographies in the Middle East to Europe, to Latin America, Mexico, Brazil, US. So we’re kind of selling all around thinking because we’re an enterprise software solution. So, you know, if I’m lucky, how many grocers can I sell to in North America? OK there’s, you know, there’s a big market there, probably, you know, a hundred probably would meet our clip. And then that’s if I want to get to 50 customers, I’m not going to get 50 percent of the North American market. So I need to go. OK, there’s you know, there’s 10 in U.K., there’s 10 in France, there’s five in Spain. And so it’s like, OK, I’m going to go get one or two customers in all these geographies. That was kind of the thought and certainly still focus on the US as the biggest market. And we spend a lot of time there. But, so we’ve been kind of growing, kind of trying to grow internationally. And I think we’re right now struggling with this. The fact that we’re so disruptive, you know, that’s the tough part of the sell. So getting the product market fit, you know, I think we rode the AI shiny bauble wave. You know, everyone was excited about three or four years ago about AI. And so we got a lot of growth from that. But now it’s like, you know, we’re running into the face of, OK this retailer has 500 people who do the job that our software could do and you know, that resistance and change.
Tony Safoian [00:16:18] Very sensitive right now.
Gary Saarenvirta [00:16:18] Yeah. So how do you sell a disruptive technology? That’s what we’re trying to figure, you know, trying to figure out. It’s hard to sell to those people who you may be altering their job description. You know, it’s hard to do that. Right? So.
Tony Safoian [00:16:32] Definitely. Look, and there’s going to be some new jobs created by virtue of – not 500 of them, you know?
Gary Saarenvirta [00:16:39] Yeah, absolutely.
Tony Safoian [00:16:41] That’s the challenging part. But, you know, at the same time, I think there’s sufficient pressure, especially in retail, to completely reinvent. Right? Completely have a better understanding of the customer experience, customer’s needs. Distribution models are being – online versus delivery, home delivery, retail curbside, you know. So I think in some ways I think it sounds – bigger role to play in a retailer’s desired operation than ever before.
Gary Saarenvirta [00:17:13] Yeah.
Tony Safoian [00:17:13] Because they actually have to transform now. Isn’t that, don’t you also feel that demand push?
Gary Saarenvirta [00:17:17] I feel that demand totally. I mean, I think, I mean I wouldn’t wish the pandemic would have happened, but I think it’s accelerated a lot of technology change, you know, brought it forward a decade, right? And so I see automation as a huge requirement in retail. You know, the retailers are overwhelmed with their e-commerce channels, which if you had been an omni channel now that’s all of a sudden grown maybe by an order of magnitude or close to that. And you have to deal with that and your regular business. And on the insurance side, consumers want to be reimbursed in real-time. And, you know, insurance has been digitizing already for a decade. And I think this is just accelerating it. And as we get consumers that are more and more savvy and we love our smartphone apps and how slick and easy they are, we want everything in our lives to be like that. And so I think there’s pressure in all industries. And so we see that opportunity for sure. And it’s just, you know, we’re still a relatively small company, 50 people here, 15 customers. So it’s, we have this story to tell. And so how do you get out there? And, you know, we’re in this cusp of disruption that’s happening. And we’re not the only company that’s running into this kind of disruptive change requirement where people step sideways, don’t leave the building, but they kind of step aside and let machines come in and take over some of the tasks. And I think that challenge is being faced in many industries, in many different types of technologies. And I think once humanity figures that out and we’re comfortable with that and realize that the machines aren’t taking over, they’re not destroying us, it’s good. You know, I think then a lot of us will really ride forward and hopefully we’re trying to help make that happen, you know.
Tony Safoian [00:18:56] The efficiency potential is still great in many industries. A good friend of ours came from the Google – many years ago, and because they thought the way credit rating worked was highly inefficient and inaccurate, right? And the insurance industry, there’s all these new insurance, you know, as you would sort of disruptors coming up, some being acquired by the traditionals, but like the way premiums were set, right? Was maybe not very – and could be optimized. So I think all these traditional distribution modeling challenges, I think are still very ripe for disruption. And it feels like, again, I agree with you, we’ve seen the same thing in terms of our company trajectory is like, don’t wish to – if there was ever a compelling event that would accelerate traditional conservative organizations in their digital journey, who thought they had five to ten years to do this, they no longer do. And we think that there’s a lot of positive sort of – potential eBid impact potential in, you know, the Fortune 2000 if some of these things are implemented better.
Gary Saarenvirta [00:20:17] Absolutely. And we’ve seen in our customers, on average in retail, we’ve seen a three to five percent total company sales lift. You know, so if you’re in a one percent net margin industry, we could double net profit now getting the people to buy into that, like, you know, that’s the hardest thing. But I see that in every single retailer we’ve gone to from our smallest clients on the order of 100 million in revenue and our largest clients, you know, 30 billion in revenue, we’ve seen the same types of metrics everywhere. Now, I’m not going to have my customer come to me and say, hey Gary, you made us a billion dollars. Like and you know, I’m not going to hear those words, but we know we’ve contributed through continual contract renewals, that there’s value there. And the change is huge.
Tony Safoian [00:21:01] – by the way, to measure the impact of the work that we do, right? Like even in our space where we’re generally providing like the infrastructure and the plumbing.
Gary Saarenvirta [00:21:08] Yeah.
Tony Safoian [00:21:08] And the services around that. Like I’m sure you’re getting pressed to deliver exactly the kind of data that warrants a renewed agreement, just like – are, and I think that makes sense. It’s the, you know, maybe you had a few years where people are doing AI because AI was cool. But now it’s like – the lift, you know, demonstrate that the savings or the increase in revenue and for those not familiar with retail, one to – is a crazy lift, like it is a remarkable amount of lift.
Gary Saarenvirta [00:21:47] Yeah, and when your net margin is one percent or close to zero, you’re flat. You know, like I mean, we can double the net income of a retailer. And similarly, on the insurance side, it’s you know, I think that in you know, there’s 10 to 25 percent fraud, waste, and abuse in typical insurance businesses, you know. And so we’ve been able to identify millions of dollars of fraud savings. And the barrier there is there’s, insurance company has a human being has to look at every complex claim or fraud case to adjudicate it or decide if it’s fraud. So human beings are their bottleneck, there’s not enough of them, right? So most claims just get paid. And so that affects the cost of insurance for you and me.
Tony Safoian [00:22:28] Right. It’s easier to pay it then to adjudicate it, you’re right.
Gary Saarenvirta [00:22:30] Exactly. And so, you know. Yeah. You’re getting a 500 dollar windshield claim. Are you going to spend time on that, you know? Like or you know, so they spend time on 100,000 dollar accident.
Tony Safoian [00:22:42] If it costs you 1,000 dollars to investigate it. You’re probably going to just pay it.
Gary Saarenvirta [00:22:44] But at the end of the day, if you look at what’s been the largest factor driving the cost of insurance in the last 25 years, it’s fraud.
Tony Safoian [00:22:53] Fraud.
Gary Saarenvirta [00:22:53] Right?
Tony Safoian [00:22:53] For sure.
Gary Saarenvirta [00:22:53] You know, there used to be something like I think five percent of whiplash injuries were like a grade five injury, you know, which is the worst, most severe. And, you know, 80 percent were like grade one or two. I think now it’s like 80 percent are grade five. You know, it’s like because people have realized that, you know, this is an easy system to game. And, you know, that’s why I started the company. I thought that fraud thing was such a home run. But it’s just a willingness to go chase that. It’s again, it’s a tough change. You know, tough if you’re the CEO of an insurance company to admit that it’s happening on your watch. And, you know, it’s a tough, tough change.
Tony Safoian [00:23:29] Look, I think that there’s going to be enough pressure in terms of digitization and automation that even the most I think conservative and resistant leaders have to go down that path because their boards and investors are going to push them.
Gary Saarenvirta [00:23:42] Yeah.
Tony Safoian [00:23:42] To do that because we – paid up legitimate claims quickly, because at least that is critical, right? And we definitely don’t want to pass on the cost of – onto our great customers, and we want their premiums to be low and competitive. But in retail, I mean, I think more than any other industry they’ve seen, obviously there’s been know travel, hospitality has been hit really hard. And maybe there’s things they – process for sure there’s just nothing you can do when literally you’re locked down. But retail has transformed the most for those who had the foresight and the ability to execute. And by the way, over the last year, year and a half, like we’re in the business of delivering these types of solutions to customers. We’re in the business of selling technology like video conferencing technology with Workspace and other things, communication, collaboration tools. We were just actually, and I’m sure you’re in the same boat of like, holy cow what if this pandemic had hit 10 years ago?
Gary Saarenvirta [00:24:48] Oh yeah.
Tony Safoian [00:24:48] If we thought the economic impact was tough now, imagine if you couldn’t – or get stuff delivered, or collaborate, or video conference. Like, a lot more parts of the economy would have shut down.
Gary Saarenvirta [00:25:09] Absolutely. And I say, isn’t it like, that’s the benefit of technology. Like if Zoom hadn’t existed, what would we have done? And you thought, what’s the value of zoom or teleconferencing? Now ask that question today, right? It’s you know, so you look at it, so what’s the value of automation and building more stable business? Say, well I get it done today with my people, but then the pandemic hits and, you know, like, I totally agree with your point. You know, I think that’s, you know, it has to change. And I think, you know, sometimes technology’s overlooked in some industries more than others, you know, are a little bit more resistant to investing.
Tony Safoian [00:25:47] And here’s a challenge, because human memory timeframes are like so short. Here’s the challenge, the challenge for all of us, us, you and I, as leaders in the community – services and technologies like to make sure that once things get better and open up, people don’t naturally default to all the old habits and the ways of thinking. Because I think more than anything what 2020 showed us is that we must be prepared for everything, right? Every possibility – a disaster, this is not going to be the last pandemic. So I think we’re trying to encourage our customers to like, hey, you know, the muscle memory you’re developing now, like don’t go back. Like curbside pickup will probably now always be an option and it should be, right? Don’t go back to like, we’re done with curbside. Everything’s in store now – trying to encourage in our customer base.
Gary Saarenvirta [00:26:41] Yeah, I agree with that. I think there’s been a lot of great services and, you know, e-commerce has risen like crazy. I mean, we’re not going to stop, yeah. Consumers don’t want to stop that, you know, and the businesses should continue to support that. It’s all about servicing your customers, right?
Tony Safoian [00:26:56] Exactly.
Gary Saarenvirta [00:26:56] And ultimately, our technology helps our clients service their customers. It’s like if I elevate your employee to free up their time, they’re going to spend time servicing their customers, delivering on their mission, giving value to shareholders. So when our software enables a three to five percent sales growth, it’s not our software, it’s that we freed up our clients’ employees. They delivered the three to five percent. We just supported them to do that. Right? And that’s the technology is an enabler, right? It’s a support vehicle. But the people who live there, they’re the ones who get it done, right?
Tony Safoian [00:27:28] Totally. The technology itself.
Gary Saarenvirta [00:27:32] Sure.
Tony Safoian [00:27:33] Because, again, you weren’t born in the cloud, you know, there’s no cloud 20 years ago and probably 10 years ago, that was not like as mainstream as even though, you know, Amazon had a huge head start and stuff that they had. Tell me about your tech stack journey and how you, maybe how it was when you were just doing services, how it evolved when you were kind of becoming a SaaS solution. That’s really an interesting story I want the audience to hear as well.
Gary Saarenvirta [00:27:59] Yeah, for sure. I mean, you know, when I worked at – just some funny statistics, when I worked at Air Miles, like the loyalty program, 170 retailers in Canada. So 80 percent of the population of Canada were collecting their transaction data. So like, right? And so it wasn’t the detailed t-log detail, but it was all their like, one record per transaction. And so, and we had a refrigerator sized server, IBM P series. It wasn’t called a P series back then. It was, I forget what, it was an AIX server and it had like 40 gigabytes of disk space, right? And we thought, wow, that was – so that was when I started my career, right? And, you know, we’ve evolved into parallel computing. And so we were doing kind of this machine learning, parallel computing on, you know, hundreds of gigabytes of data at the time. And that became terabytes quickly when we got into grocery. And so I took my experience working with parallel DB2 and parallel hardware. And so we had our own equipment when we did professional services it was always taking the clients detailed transactions. And so our tech stack was built on parallel computing, DB2, then we got into some opensource. Because when you’re getting into, you know, like five, 10 terabytes of data the DB2 licenses were a little too expensive for a small company, right? So we kind of moved from there to start to look at kind of Hadoop and these opensource kind of databases. And so we moved to Hadoop, even though, you know, running DB2 and Hadoop on the same query, the same hardware, you know, DB2’s got way more investment dollars, but at the end of the day was free. And we worked to overcome some of the challenges. But, you know, and we built a lot of capability there. And then eventually – and we managed our own GPU. So we did, you know, MPI parallelism first using, you know, multicore processors and doing parallelism on that. And then, you know, GPU came out and we started playing with Invidia GPUs and putting our software parallelizing that. You know, in one hour, one of our smart young guys, graduates of the University of Toronto Engineering Science Program, where I went to that program and we hire a lot of people from EngSci. And I said, OK, here’s the book on GPU. Here’s my crappy code that I wrote that parallelize it on NPI. And I think it’s really easy to do this. And you know, four hours later, the codes running a hundred times faster because it went from running on, you know, four, 10 core processors, to running on a GPU of 3,000 processors, right? And then we said, OK, well how do I scale from here? I’m getting more and more customers. I now have 100 terabytes of data. We’re managing our own off-lease hardware servers, break-fix, popping in drives. And so I’m starting to build all this core competency and hardware management and we’re trying to write parallel computing software. And I’m going, okay, this is not making too much sense anymore. So I thought, you know, we should look at this thing called the cloud, right? And so kind of that’s where, you know, we hired some – providers that –
Tony Safoian [00:31:06] What year was this? What year was that pivot?
Gary Saarenvirta [00:31:07] Yeah. It was that pivot. It was that pain of managing our own infrastructure and how long it took to deploy another server when we got another customer. And then we said, doesn’t make any sense to be building core.
Tony Safoian [00:31:16] What year was that?
Gary Saarenvirta [00:31:16] That was really like, couple of years ago, right? Like we were doing this until like when we started to really move to the cloud, we started exploring, you know, we started playing with Azure like maybe three years ago. And then, you know, couple of years ago decided let’s go to the cloud. And we, you know, did you know, explored Azure versus Google. You know, those are the two choices. You know, being in retail, AWS was a bit of persona non grata from our retail customers.
Tony Safoian [00:31:44] Oh yeah. We hear that all the time. For all of our retail SaaS customers, there’s just no go, no go on AWS.
Gary Saarenvirta [00:31:48] Yeah. And then we kind of did a, you know, kind of an RFP and a bake off and kind of moved to Google, right? A year ago with your guys’ help. You know, we used SADA here to help us with the migration. And, you know, we’re kind of almost fully in the cloud now. It’s taken about 11 months to migrate. We’re migrating our last customers. So we expect to be done the end of next month and then really focusing on kind of becoming cloud-native. I’d say we kind of forklift upgraded our infrastructure in step one. And step two is to get cloud-native. And, you know, my goal that I challenge my technical team is, I want to run my parallel software that we all developed together, I want to run that on a million cores. Can we? We could do that, like, I want to run that test and, you know, I want a real-time optimize for my clients. Because, you know, and when retailers when we deliver, here’s the products you should promote this week. And my client says, well, what if I swap that one product out? What happens? I want to push the button and give him an answer. I want to spin up a million cores and give him the answer and charge them 20 bucks for that enter key. You know, like, you know, that’s where we want to get to, right?
Tony Safoian [00:32:56] When it costs you like 50 cents and you want to charge 20 bucks. Like, that’s the model, right?
Gary Saarenvirta [00:33:01] Yeah, I mean that. And that’s where we want to get to. And we want to take away the headache of infrastructure management, which has been a barrier to our developers. Oh my God, this hardware thing is broken. We’ve got to get someone to fix it. And so it’s been a huge headache, but.
Tony Safoian [00:33:16] So you’re going to have a really exciting kind of a re-platforming journey ahead, you know. And is BigQuery sort of part of that?
Gary Saarenvirta [00:33:25] Yeah, we see ourselves moving to BigQuery and Kubernetes. And, you know, the interesting thing, my son works for Google and he’s a cloud engineer on our account, right?
Tony Safoian [00:33:34] Yeah I saw that.
Gary Saarenvirta [00:33:34] So it’s kind of funny, we just had a QBR today just before this call with the SADA and Google team. And so watching my son present is kind of a weird feeling. It’s kind of, wow, my son’s got his shit together, he’s like smart. And I’m also his customer. So I’m kind of, it’s a really you know, I took a picture of the screen. I took a picture of the screen –
Tony Safoian [00:33:55] He must feel, it’s like, oh my god, this is my dad. He’s judging me right now. And he’s also –
Gary Saarenvirta [00:33:58] And I took a picture of the screen and I texted it to my wife. I go check that, right?
Tony Safoian [00:34:05] It’s also like, pat yourself on the back a little bit, right? Like, mission accomplished. Good dad vibe right there. No, that’s incredible. I think what you’re describing is the stuff that we really get excited about. Because the reason that we went all in with Google is that we saw the Google path as being innately more transformational than the other – virtue of being number three, by virtue of being very good and heavily invested in the serverless ecosystem. We’re seeing more Hadoop – migrations than ever before. And I’m talking about massive scale, because most of these Hadoop customers, like Twitter used to run on Hadoop.
Gary Saarenvirta [00:34:47] Yeah.
Tony Safoian [00:34:47] And so they move to, you know, by and large part to the Google infrastructure and platform services. We’re doing many other projects like that, like huge -. The same thing you went to, like when the data set got so big, the licensing fees on any other commercial database made no sense. They had to go open source, but then – DC-based customer like we’re testing query response times and Hadoop versus BigQuery, 80 times faster, 100 times faster. It’s just -. But those are the kinds of things you can utilize to build new capabilities for which your customers will be happy to pay for. But also in general allows your solution to kind of keep up with customers’ expectations of what they see in the consumer software world every day.
Gary Saarenvirta [00:35:36] Yeah. Yeah we’re excited about this, you know, we’re super excited to get on getting 100 percent cloud-native and really taking advantage of these technologies, getting serverless, you know, being 100 percent ephemeral, you know, that excites me. And the capabilities that brings, the ability that we can scale to any workload. So excited, and that helps us push our capabilities and deliver these new features to customers. Exactly as you pointed out. And that keeps us ahead of the curve.
Tony Safoian [00:36:03] You’re just doing, you worry about the code and of course, you know, UX, UI, all that beautiful stuff. But you’re just not even worrying about the infrastructure. You can bring on as many customers as you need. They can get as big as they need to get. You can charge them whatever you need to charge. Also in your global ambitions, again, I think picking Google is – of presence and a network speed and latency in the Google cloud globally is literally unparalleled. So there’s also data – and data residency needs. I mean, they just opened up the Poland data center. But they, you know, I think they’re Montreal now, which has its, you know, different things in Quebec, different states in the United States all around – Asia, Africa, etc. And that’s going to get really exciting because I think data residency –
Gary Saarenvirta [00:36:50] Yeah, that’s one of the reasons we picked GCP was just, you know, the global presence. And I think also you guys were a big part of the reason we picked them. You know, when we did the Bake Off, you know, you guys were really impressed in terms of the migration team. The technical talent you guys brought to the table was like, yeah, we want to work with these guys, you know, and –
Tony Safoian [00:37:07] I appreciate that, and I feel like we’ve gotten better in the last two years as well, and I’m so honored that we were part of that first big leap. You had to take from on-premise to a cloud, and we were part of that decision to help you choose Google Cloud. That’s what we’re really proud of because I mean, what makes me proud of what I do is we truly believe we’re making an impact to customers and to decision makers who are choosing this path. And just like – passionate about your work, because, you know, the impact Daisy Intelligence has on your customers and the people that work there and their businesses, it’s really meaningful work. And I feel like it’s still very early stages of, you know, applied A.I. in retail and these other industries, just like – cloud, I mean the Daisy Intelligence story is very common. Our number one vertical, and now we define it as a vertical where two years ago – literally SaaS companies are like the number one customer for Google Cloud and in a lot of ways our biggest vertical at SADA. And we like, when I was on with PacketFabric on the last episode, and I was like, you know, the thing about Google is, you know, they don’t want to be in your business. They want to provide the Lego pieces for you to build your business. And I think that is just a different sort of orientation towards partnership than some of the other cloud providers have.
Gary Saarenvirta [00:38:40] Yeah, that’s cool. Yeah, no, we’re super excited, our team is excited to use the modern technology and tools and learn and, you know, young technical people want to learn and have a career path. And I think this is the right move for not only the business that’s for the people in the business as well. So it’s exciting. It’s fun, fun for them. And yeah, I think we just see great upside continuing forward on this path, so.
Tony Safoian [00:39:06] Totally. Well we hope to be your partner for many, many years to come. Thank you for spending some time together here, Gary, and educating the market in US, Canada, worldwide, on your career path, Daisy Intelligence story – and how Google Cloud has helped you transform the way you go to market, that’s awesome. These are exactly the types of stories that people want to hear directly from founders like you. So I really appreciate you being my guest.
Gary Saarenvirta [00:39:31] I appreciate that. And thanks for helping us get to the cloud. We really appreciate the support your team has given us. It’s been a great year so far. And we look forward to many more.
Tony Safoian [00:39:40] Awesome, talk –
Gary Saarenvirta [00:39:40] OK, take care.