 Good morning, welcome back to theCUBE. The leader in live tech coverage covering day three of Snowflake Summit. This is actually their day for our day three. Lisa Martin, Dave Vellante here. We've had some awesome conversations as we always do. We're going to be teaching you how to become a query boss, Dave. Did you? Query's really interesting, right? Because we've been talking all week about how Snowflake has many different query options. You know, they started with SQL and added data frames and now it's a search with Neva and NLP and stuff they're doing with NVIDIA. So it's really interesting to see the expansion of the platform. It is. Being coming a query boss, we're going to be learning how to do that. Jacques Nadeau, one of our alumni joins us. He's now the CEO and co-founder of Sundeck. Jacques, great to have you on the program. Yeah, thanks for having me. I really appreciate it. Talk a little bit about Sundeck and query engineering. I'd love to know about the name and about Flow, your mascot. Yeah, absolutely. So Sundeck is a relatively new company. We started a little over a year ago. We actually just launched our product, came out of stealth about four weeks ago. And we're focused on query engineering. And query engineering is about, really the art and science of getting your queries to work better for your organization. And there's a lot of different ways that that can impact an organization. So one of the simplest ways that people understand is that you want to make sure that for each query that's running, you're getting the best efficient use of resources, right? And so trying to figure out how you can use, in the case of Snowflake, warehouses more effectively, how you can use different kinds of patterns inside of Snowflake effectively, that's a pretty obvious one with query engineering. What people don't necessarily initially realize is another thing that's where engine can do for them, is that in organizations you, especially data driven organizations, you have larger and larger communities of users actually interacting with data. And so while there are a group of users that may be highly sophisticated in their use of data, there's a lot of users where data interaction is only a very small part of their job. And these users often make mistakes. And so there are tools like cataloging tools that help you to try to remember how to work with data effectively. Unfortunately, those are kind of offline. And so if you make a mistake, the biggest risk you can have for an organization is that these people interact with the data, they make a mistake of how to access the data, and then they take that to be fact and start making conclusions from the business based on those incorrect assumptions. And so query engineering actually operates at the layer right when the query hits the data cloud, watches those queries and actually can intercede and say, hey, you know what, you actually didn't do this correctly. And so once you correct what you're doing or potentially automatically correct what they're doing, so they don't come to the wrong conclusion and then impact the business in a poor way. The question is jumping to my mind is, isn't Gen AI going to take care a lot of this? Or are you Gen AI? So it's a great question. So the biggest pattern you see today, right, is you see LLMs and AI basically create a new way to create lots of additional queries, okay? And so what you're doing is you're actually lowering the bar of sophistication of users to be able to access the data. Making the problem worse. Yeah, so it's actually making the problem worse. Is you're making it easier for people to just generate really, really large queries that are going to be both inefficient and also like how do you know that the Gen AI got the patterns correct, right? And so that's great, it's actually helpful for us. We actually think it's very exciting. Is that in part why you started the company as you sort of saw this happening and said, okay, this is going to be even a bigger problem than it is today? Well, so it was a couple of things, right? So one was is that over the last several years, I've worked with a lot of large data organizations. And what we started to see is actually organizations build bespoke solutions to solve this problem. And so especially in financial services and healthcare, we've seen a number of different companies who try to cobble something together to solve these problems. Now, just like any kind of internal technology, they're underfunded, they're poorly built, but they just don't have enough resources and time to really make them successful. And so they solve the narrowest possible way of solving this problem. And so that was the first pattern. But then the second pattern is exactly that, which is that all we're seeing is larger and larger communities of people working with data. And the larger that community is, the more there are people who are less sophisticated and less day-to-day working with that data. Are there technologies that Sundeck is replacing? Really no, we're creating a new category. And so the only technologies I'd say we're replacing are those situations where people have built bespoke solutions to solve this problem. So we're excited about creating a new category. It's challenging to always create a new category, but we find it to be also really rewarding. We've been here the last few days at the summit on the floor and the interaction and response has been just marvelous. Not only from people who use Snowflake, but a lot of the team at Snowflake themselves. So the AEs and SEs coming from Snowflake are often saying like, man, I hear this every day and it's great that you guys have a solution to help us out. When I talk about, again, we've been talking all week about the numerous query methods that Snowflake is supporting. I presume in the one hand that makes the problem worse. We've got a lot of different people using it. Analysts are doing SQL, they're doing Python, data frames. That's how Python programmers talk to data. They're probably pretty good at queries, but maybe not, I don't know. And then, like you said, NLP just makes this a nightmare. Yeah, yeah, no, so it's not only people who are writing queries themselves, right? It's all the tools that are generating queries, right? So most organizations have 10, 20, 50 BI and other kinds of technologies that are accessing their data cloud. And all of those things, people can make mistakes in those as well, right? And so it's not just about like, is it efficient or not? Like it's about like, oh, am I doing this pattern correctly? Or is there a way I can get this much more faster, right? Or more up to date, right? Like there's always this question of like, how old is this data? And is it going to be the best version of what I'm getting? So what are you doing with Snowflake and where do you fit into that whole value chain? Yeah, yeah, so the pattern is we basically sit in front of the data cloud and can pass queries through but then also intercede and the focus is really around data engineers. We recognize data engineers as basically the greatest new collection of creative people sort of in this data ecosystem, right? And we see a lot of that exciting creativity in the context of DBT and the rise of analytics engineering. And so we're working with those same users in this context and we engage in a couple of different ways. So the first is that as I said, we sit in front of the data cloud and allow you to do this interception. But the second thing that we actually announced here at the summit and we're a launch partner with Snowflake on is a new native app. So we built a native app called Ops Center for Snowflake and this came out of primarily our own experiences with challenges around understanding consumption of these technologies, elastic compute technologies. And so we built this application. We started by building stuff for our own purposes and then realized that every customer we talked to was struggling with the same kind of thing. And so, you know, I've worked in open source for the last 20 years and I'm very passionate about building communities where there's a common sort of goal and need, but it's not really something that makes sense to monetize. And so we actually not only created the Ops Center project as a free project inside the marketplace, but we also made it available on GitHub. So not only can people take advantage of that, use it, they can also contribute back to it and we can extend. And so that people spend less time thinking on a day-to-day basis about the consumption challenges of working with something like Snowflake. What was it like building a native app? What did it sound like? It's a great question. It's rewarding and it's rewarding because as a small company, it's hard to sell to big companies, right? There's, you know, we're new. How much trust do you have with a small company? And what native apps gives us is the ability to basically provide something to a very, very large enterprise in a way that they're very secure. So a native app runs inside of their Snowflake account. No data leaves their Snowflake account. We don't have access to any of that data. And so it allows us to establish a substantial amount of trust as a small organization with these large organizations. So what was it like raising money in the past year? Well, we were very lucky. I guess that's what I would say. So we actually raised some of the companies in this space between the time that we signed our term sheet and got our money had lost 50% of their valuation. So we raised that exactly the right moment, I guess I would say. Having conversations more recently, I think it would be much harder. Okay, and so you've raised, is it correct? You've raised about 20 million, is that right? And I presume you hire an engineers. It's really where you're focused on. And a head count today? Yeah, we're about 15 right now. Okay, so really focused. So you got plenty of capital, at least for now. Yeah, absolutely. Yeah, no, we got five years of runaway right now. Yeah, you're not spending it on promotion at this point. So okay, so that partnering with a Snowflake helps elongate that runway as well. Absolutely, it accelerates our ability to do things right? Like obviously they've got people out there in the field everywhere, right? And so if we can give them a solution. So it was one of the hypotheses of the company is that I had worked at Drumeo before and one of the things I saw was is that people at the edge, they're actually trying to get deals done and try to solve customer problems. They need more power tools. They need more tools to actually be able to change what's going on with the data systems they're working with, right? Like you can open up a feature request to try to enhance something, but when you're talking about a massive, powerful platform like Snowflake, it's going to take some time to enhance it and it's probably going to be a fairly narrow version of that. And so if you can give both data engineers and what SES are, which is effectively like, you know, part-time data engineers to help their customers, some kind of capability to solve these problems, that can work very, very well. Are you hitching your wagon to Snowflake and exclusively or not necessarily? You are. So for now we're entirely focused on Snowflake. Like you know, who knows what the future will bring. Yeah, but that's smart. Start, get a foot in the door and see what goes. It's an awesome platform and has a huge amount of adoption. What are some of the opportunities that you see in the data cloud the next year, three, four years out? Well, the most exciting thing about Snowflake is this opportunity to push into what is the data cloud and what can that become, right? And so I actually think a lot about Salesforce in this context, right? Like Salesforce went from an application to a place where huge amounts of applications run inside of that ecosystem. And it was because they had sales data, right? They had sales data and everybody wants to build applications around sales data. Well, Snowflake is just 10x that, right? Because there's all the data is inside of Snowflake. And so the thing that they have as an opportunity is to be able to create that same kind of ecosystem but around all the different sort of sub-industries that are working with Snowflake data. And so I think that that's the exciting part. Now becoming a developer company, right? Which has historically been what I would say is more of a data engineering analyst company. I think that that's going to take some time. But I think that that's the most exciting opportunity. So you're developing in Snowpark, is that right? So some of it's in Snowpark but it's also in the native app framework which in part is Snowpark. Okay, so what's that been like? What's that experience been like? Has the maturity as a customer slash partner? I would say, well, public preview started at Summit. So it's young. I would say that definitely we learned a lot along the way and you had some bugs and whatnot. But it was also very pleasant. Like it's built for people who work with databases. And so it worked well for that. I think that one of the challenges that we saw was we wanted to customize things more and really enhance the user experience. And right now it's a little bit constrained in that respect. And so the benefits far outweighed the challenges that we saw with it being that you can get into these large organizations without having to go through the same cybersecurity efforts that you potentially otherwise would. But there is definitely a lot of things that can be taken to the next level as well. So the hardcore techies are going to want more sort of hands-on access to tooling. How does that affect Snowflake's promise in your view? I mean, they have to be careful about their governance and their security and that is what takes forever for that. That's why we still don't see Unistore in public previews because it's hard. It is very hard and it's an excellent question. So they launched container services in a private preview at Summit where you can run arbitrary code. And so what they did with native apps is they basically said you can't get to the network and they made that a very, very tight system. And that keeps your data in, right? But the moment you give people arbitrary code running inside of Snowflake accounts, it's going to be a different level of challenge, right? That's exactly what you said, which is like, if you let them have arbitrary code, they can also go out to the network and it can see the data, you have to really think about how that is different than running outside the Snowflake cloud. And so I think that that's going to be the challenge is like providing that substantial amount of flexibility, because developers have a lot of tools that they want to work with today, right? You know, Python and Spark, or Python and Java, and JavaScript are the three options you have inside of the sort of like the closest part to the data system right now. But you know, developers like a lot of other languages. And so, yes, you can run these things in kind of container services, but I think that that's going to be the thing that's going to be really challenging is to figure out what's the right balance between the governance and the flexibility that developers want. And they'll add more and more of those over time, but you've got to make sure it fits into the framework. What are the similarities and differences with the sort of app store and the iPhone model? Well, I think that the similarities are is that it feels very much the same. Like you go into the app store and you click something, I think that one of the really big differences, and then what we see is a little bit of a challenge, is that it is patterned around administrators, right? So like when you, everybody's got their own phone, they can install stuff on their own phone. Sure, there might be like corporate mandate and some of your phone, but you can also install your own apps onto your phone. And right now you don't have the ability for, say a random analyst or data engineer to install apps inside of Snowflake. So I say that that's pretty much the biggest difference, that and then sort of like the constrained flexibility. Do you think that will evolve as the ecosystem grows and demands that, or is that antithetical to that whole promise of governance and security or don't know yet? I think it's a good question, right? Because I mean, there's like, you know, Snowflake has a really rich RBAC model for security, right? And so, you know, as long as you don't violate that model, why couldn't others install the apps? So I think that it could go there. I'm not sure that it's a natural tendency for people to go there, right? Like, you know, one of the things that have traditionally been true of data systems is that administrators have the ability to create things that many other users don't have the ability to do. And so I think that that may be something that they'll have to figure out how they sort of, you know, navigate that. So what are your big milestones? You know, you're at the board. Here's what we're doing, folks, boom, boom, boom. Yeah, yeah, yeah. Well, I mean, we just hit a couple of them, right? We just launched our first, our SaaS product four weeks ago and we launched the native app here. From here it's just making customers successful for their foreseeable future. Like, that's all we're focused on right now. And really we believe that something, so one of the things I've seen with Query Engineers is generally because it is bespoke solutions, it is often limited to larger, larger organizations. Others can't afford to put a team of developers against this problem. And so we want to make it, you know, broadly available, right? And so any data-driven organization is going to be more and more struggling with this challenge of, like, how I make these queries work the best for me. So you're not worried about go-to-market fit at this point. You're trying to nail product-market fit. Once you nail that, in a way, it will take care of itself with Snowflake, because that's a really smart way to start. And then who knows, the TAM can expand from there. Absolutely. Yeah, awesome. And what customers are you working with? Don't have to mention my name, that you're really excited about in terms of really getting the value out of it. Yeah, we've got really good engagement with actually a number of very, very, the largest financial services customers. So we've got some good engagement there, as well as a number of people in retail. And so both of those are looking really, really positive. Awesome. Joach, thanks so much for joining us on theCUBE, talking to us about Sundoc, sundoc.io, what you're doing with Snowflake, and how customers really can become query bosses as your website says. I love that, by the way. Awesome. Thanks so much for your time. Really appreciate it. Great to have you. We want to thank you for watching for our guests and for Dave Vellante. I'm Lisa Martin. Up next, our final segment for Snowflake Summit 23 with CUBE alum and Snowflake CMO, Denise Pearson. She's going to be breaking down the event. It's differentiators. How they will extend this event past the four days, and she's going to be dropping some news about next year's summit. You can only find that here on theCUBE. Catch all of our content on theCUBE.net, and an analysis and editorial on siliconangle.com. And we'll see you in a minute. You're watching theCUBE, the leader in live tech coverage.