Conference Transcript - SNOW 2026-09-08

Gabriela Borges, Analyst — Goldman Sachs

All right. Fantastic. We will go ahead and kick off the Snowflake session at the Goldman Sachs Communicopia Conference. I'm Gabriella Borges. I lead our software franchise. Delighted to have with me on stage Sridhar Ramaswamy, CEO. Brian Robbins, CFO, thank you both for being here.

Sridhar Ramaswamy, CEO

Thank you. Excited to be here.

Gabriela Borges, Analyst — Goldman Sachs

Sridhar, I want to start with some of your conversations in the field. Tell us a little bit about what you're hearing. If we look at the modern data tech stack today versus 2024, 2025, the pace of innovation has changed. So tell us a little bit about what you're seeing in those conversations and hearing in those conversations about the customer journey to go from old to actually new, meaning AI-enabled.

Sridhar Ramaswamy, CEO

There's always been a lot of demand for data modernization. but you know the word migration strikes terror in the heart of pretty much every CIO or CDO honestly like everyone just takes forever highly uncertain outcome and so on. I think AI is having a pretty profound impact on how quickly you can get those done and expectations not just from you know from me for my team I've talked before about how I want migrations to be mostly automated but even customers are expecting it we have a very large manufacturing client for example do a teradata migration planning aggressively to finish it in less than three quarters is not something you would have heard of in 2024 that's like that's part one of a lot more is possible let's go get it done but what is equally interesting is now the ability to have conversations at a data platform level at the level of snowflake we just stayed out generally of a lot of these kinds of conversations is having them about how we can deliver business value it is everything from like how can we automate invoice processing at a really large energy manufacturer because processes like this they're always super manual super spotty they would do like spot checks here and there they estimate that on 10 billion dollars that they pay out every year they'll be a percentage point more efficient except that that's an astronomical amount of money it's talking about that or talking about supply chain optimization or talking about how do you implement a custom CDP a whole lot faster it's having conversations like that that I think are very very distinctly 2026 compared to the previous one where honestly most CEOs wouldn't even bother to talk to me. It's like, oh, data vendor, who cares? I think that change is what is remarkable about this moment.

Gabriela Borges, Analyst — Goldman Sachs

I want to come back to custom CDP, but let's stay on the migrations thread for a moment. When we came to your conference in June, a lot of the system integrators we were talking to spoke about how migrations can now be fixed cost instead of variable cost because of coding tools.

Sridhar Ramaswamy, CEO

Tell us a little bit more about the shift from variable cost migrations to fixed cost migrations and how we think about the impact that coding tools and then that's like nicely into Cocoa specifically can have on that pace of migrations I would say this is a larger trend AI fundamentally is making software industrialized and I won't underestimate even now the threat that it poses to every tech company every software company it's a profound profound shift what it has also done is it has obliterated the distance between what a data platform like snowflake is and what applications running on top of data can be now you know stuff that people build on top of snowflake will not look like your standard package sas app it'll have its own look and feel we can talk about that but the other thing that it's done is it has also squished the distance between a data platform and actually what used to be called services because you can begin to automate a lot of a lot of things and in as much as software it represents like what we humanity call intelligence that's what they do they put workflows they put data structures into place they organize our thinking AI accelerates that massively, which is why a number of folks, because they can now bring the power of coding agents, are basically saying, wait, I can compress the time of something like a migration massively, and also feel very confident that the weird problems that will come up during any real migration, the little odds and ends, can also be fixed equally quickly, and they're sensing an opportunity because the majority of the industry is still operating on time and materials, a lot of time and a lot of materials and a lot of money. And so the progressive system integrators are going, I can guarantee outcomes. This is what we do as well, where we are saying we can deliver outcomes for our customers simply because the ability to get things done fast is much better now than before, but also the ability to deal with unknown things is just also a whole lot better it's the combination of these that I think will drive a massive change through the services industry not that I think services will go away is just going to look dramatically different a lot smaller than what it did before but one that is much more tied to what are the outcomes that customers want let me ask about Coco specifically because Brian then we can bring you into the conversation as it pertains to how you think about guidance so Sridhar we

Gabriela Borges, Analyst — Goldman Sachs

started talking about, look, it's not just the number of customers in the installer base that are using Cocoa, but it's actually the depth of usage and the net new use cases that you're also solving for. So I guess part one would be, tell us a little bit about how you as an executive team push to deepen and strengthen the usage of Cocoa within any given customer.

Sridhar Ramaswamy, CEO

Yeah. So a lot of it is what we have learned ourselves. I think I've talked about this previously part of a huge unlock for snowflake the company was having a coding agent available to every single person within the company it was not a specialized tool and so we saw bursts of creativity and innovation in every department and that's been very helpful for us just to understand what is possible with with AI and the nice thing about harnesses in general and I think the reason they're going to have a profound impact on everyone including all of you is the work that you do now is visible observable within one system which also means that it is optimizable it is automatable and so we have a lot of insight into what is a customer doing what are we doing with cocoa are we doing repeat things for example we now make recommendations for here's a skill you should be building because you seem to be doing this very often and it's a quick hop from there to get our set of skills that your colleagues are using this is something you can use to make yourself more effective at work and so we can understand things like the depth of usage and then tied back to things that we can do at the end of the day life's about what's an action that you can take that can produce an outcome that you want and so we have things like hands-on labs that are proven to be highly highly effective this is basically a two to three hour tutorial run by one of our more technical people with the customer and because of that the customer gets more effective in what they do their data teams are happier they get more more work done simpler to debug annoying problems that are a part and parcel of of their life but it also gives us a clear roadmap for this is what it takes to drive truly deep adoption with each of the customers that matters to us.

Brian Robins, CFO

I'll just add on to that. One of the things that Coco has done is it's opened up the aperture to who we sell to from a persona perspective. And so a year ago when I joined Snowflake, I hardly had any customer conversations. Today, every week, I'm meeting with three to five CFOs and talking to them about what we're doing internally on Coco and what the art of the possible is. And I think there's no better way to actually expand Coco or co-work adoption by showing people how you're using it internally. And as Sridhar said, these skills that we're making can be applied to vast sets of data to our customers to actually get them started to use that. And so I think once you show them what you do internally, the art of the possible, and how quickly you can speed up things, they're extremely interested.

Gabriela Borges, Analyst — Goldman Sachs

And Brian, Sridhar used the word burst there. So look, it's a new product cycle. And you're going to have customers that are experimenting. You're going to have questions around gross retention, durability. I think you've already said gross retention is held stable even as Cocoa is scaled. My question for you as an analyst, we try to model Cocoa, and we also try to model the impact that migrations and the speed of migrations is having on your business. What advice would you give us as we try to think about some of the blue sky scenarios over the next 18 months, and how do you de-risk the forecast from customers getting really excited about Cocoa, but ultimately it's still very competitive and you've got experimentation, and could that usage pattern actually fade over time?

Brian Robins, CFO

Absolutely. It's something that we struggle with internally as well when we launch a new product. If you ask anybody how to model that, we don't have that much data. It's difficult. Fortunately, we have an amazing team internally that has been doing this for a very long period of time and have built very sophisticated models to understand what new product adoption will look like and then compares that to historically what new products have done. We'll then take that and then basically model up what a scenario is, and then we have a very wide and deep group that discuss what we'll put in guidance from that perspective. And so when we do come up with guidance for the core platform, like the migrations, it's based on observed behavior, and we have years and years of data with that and can get pretty close for the new products. We try to be a bit conservative so we don't take a month worth of data and extract that out and say this is what it's going to be like all for this year and next year. But now that we've had two quarters of data, we feel more confident in what we can extract from that observed behavior.

Gabriela Borges, Analyst — Goldman Sachs

When you and I first met, we started talking about the customer cohorts and how, look, it sometimes takes year one as the initial ramp and then year two is really when a customer gets into full swing snowflake adoption. Has anything changed as you look at the speed at which these customers are ramping?

Brian Robins, CFO

I think from a cohort perspective, if you look at all the verticals across the company, we still have the same sort of vertical penetration, if you will, in a financial services, manufacturing, government, and so forth. As far as ramping, with the use of COCO and AI, we're seeing customers ramp much quicker than what they've ramped historically. And so whether it's our partner network or what we're doing internally, what Sridhar talked about is outcome-based pricing has really built the credibility with our customers If someone comes to me and says, I can guarantee you X for this set price, and I know historically that took a lot of time and a lot of materials and so forth, like, I'm all in. And we're seeing that from a customer perspective. We do track internally how long it takes for them to get up to their consumption run rate. And we're seeing those curves get steeper and steeper and steeper. And so customers are deploying quicker. They're consuming quicker. They're using partners, us, and themselves. They're using our agents to actually do that. And so it's really exciting to see.

Sridhar Ramaswamy, CEO

And that's a lot of where our go-to-market teams have to go. Our CRO often talks about shifting right towards outcomes. It just means that Snowflake as a company and their team in particular has to focus a lot more on how do we get use cases live with customers? How do we get it to scale within customers? And what do we have to do? And it's increasingly a result of many things that used to occupy lots of time, getting ready for a meeting, doing research about what does the customer have, what's their data estate, how do you maintain it, all of that getting easier faster. And similarly for solution engineers, they would spend a lot of time building a little demo that would take forever. Now they can be conjured up kind of on demand. And so there's this big shift. We have even created basically new job functions. One of them is called an activation engineer, an activation solution engineer. They're expressly charged with what Brian said, which is how do you get a new logo to go live on Snowflake much faster than what they would otherwise. And so that is a trend that we want to keep leaning into and pushing.

Brian Robins, CFO

I would also say selling into or actually describing what we do to all these personas. is, if you go to a CFO and show them what the possible is, they're immediately saying, how do I get that up and running like yesterday? When Shreda goes and talks to a number of CEOs, they went yesterday. And so the sense of urgency around getting these results are also, you know, super fun.

Gabriela Borges, Analyst — Goldman Sachs

Let's talk a little bit about custom apps. So, Shreda, you started talking about custom CDP. And certainly there's been a debate on the application level on what is the future of applications? How do we think about packaged apps versus headless architectures versus some of the interesting things that customers are building on top of Snowflake? Some of the things that you announced at Summit, workflow orchestration, agents, and on the application layer as well. Tell us about how you see the app layer evolving.

Sridhar Ramaswamy, CEO

I mean, first of all, I think this is a time of just a lot of innovation with what is possible. Because, you know, let's face it, building any kind of meaningful application before, again, was just a hard thing to do. Now, pretty much any of us can pick up a coding agent and say, hey, I want, you know, not just a web app like an Android or an iOS app. And dealing with the app stores is the most time-consuming part of doing something like that. Now the apps themselves are easy. So we are playing around with lots of different formulations, including things like, should the notion of an application be rethought as a handful of self-evolving skills running on top of a data substrate? What I mean by, let me give it to you with a specific example. Let's say like, oh, you want an internal survey application, easy enough to imagine. What do you want to do in a survey application, especially if it's just internal? You want to know who your employees are. You want to know how you target, let's say, a particular group. You want to manage visibility into the results that are coming. It's not that complicated. Now, if you have a Snowflake deployment like we do, absolutely, our workday hierarchy is mirrored in Snowflake. So that's where you get that from. you set up a couple of tables to store surveys to store results and figure out notifications and admin does something and then an ops person says these people are allowed to send out surveys and off people go to send out actual surveys now I didn't really talk about a UI you can conjure that up on demand by saying oh if somebody clicks on this link bring up this react app for them to respond to the respond to the survey and so what would be an actual SAS procurement you know is a handful of skills that can be installed on top of data that is already sitting in snowflake it's governed you don't have to worry about you know hey does everyone have access to this data you can manage the visibility you can also do follow-up analysis on it if it's reform text and you want it on AI on it that's not an issue so you see where this is going I think it just makes many many more things possible this is not to say that this is the end all be all solution for everything but to the extent that our vision consistently for multiple years has been we want to be the place where you can bring together all of your data and get a 360 view analytic view of the data it sets us up very nicely to rethink what is an application of the future for what it's worth we think our Salesforce data also into snowflake and so if I want to create an annotation application that's not part of Salesforce but acts partly on Salesforce data and can push it back that too is possible it's a very different way of thinking about what's an application the first time I tell people an application can be reduced to a handful of skills you get a blank stare like really what does that mean and similarly these skills don't have to be static as you look at how people are using them they can get additional functionality over time they can self-evolve That's how a lot of support systems are, like my team's SRE systems are evolving. They built the first version. They built some skills, put some data. They looked at how they were analyzing it. Then they created newer skills, and they said, oh, half of these things can be automated by agents looking at stuff first as opposed to having a human look at it. And now that's a very different notion of what an application is. It is something that is evolving as it goes along. I think the world is rich with possibility, and there's just going to be a lot of innovation everywhere. And as a platform, we focus on what are like these little nuggets that we can lay out there that is going to convince some right person in one of our customers to say, here's something else that I can build with it. We learn from them and then figure out how to make it more broadly available to other customers. You see this feedback loop and where it's going.

Gabriela Borges, Analyst — Goldman Sachs

Let me ask you on the skills side. So this is a little bit of an orthogonal question, but it's so top of mind in the last three months. Do you have a view on how the ecosystem will evolve between open source, open rates, and frontier? And does that impact how you think about your business strategy and dynamics-like skills?

Sridhar Ramaswamy, CEO

I mean, for a company like Snowflake, the more competition between our suppliers, the better it is. I mean, let's say it's the same for you. If, like, Anthropic is the only one making great models, you're in trouble, I'm in trouble. We're all in trouble. and the fact that open AI is creating amazing models is good for the world it's good for them it's good for us as well I look at open source the same way I think innovation here presses the foundation labs to innovate even more and I think as a phenomenon this is great for us it also feeds really well into the like the snowflake narrative of we are truly a cross-platform solution we are one of the few people that can tell you you can run on AWS and you can effectively run exactly the same deployment on Azure with not a whole lot of work and if you want to do disaster recovery between these instances because some regulators on top of you saying you can go down if AWS goes down that too is possible with snowflake we look at models the same way it offers up lots of options for choice for optimization and the thing that I think is unique about this moment and it's not a good or bad it's just a strange happenstance of the moment is that none of the model makers so far other than something like a chat GPT which does have true consumer lock-in have been able to create that kind of lock-in well into a pretty massive investment cycle every smart engineer knows that they can move instantly from a cloud code to a codec not a problem or vice versa my team moved over from being heavy cursor users to cocoa users on the solution engineering side without me having to harangue them which is normally how like things work with situations like this I think that's also pretty unique which just means that something that can interoperate between these models is a pretty cool thing pretty cool thing to have and I think skills themselves are the great equalizer because they're English it means that every model is immensely capable of taking a skill that perhaps was written for a different harness for a different model and figuring out how to tweak it to work in a new situation I think this all makes up for robust choice for all of us I think this next question is for both of you all so strategic value of selling inference posture into your install base versus potentially a lower gross margin how do you think about that trade-off I mean first of all you know it depends I hate to start like this but it depends on what inference is if it is merely reselling kept on differentiated capacity from a large supplier you're not creating any value that's like fake news on the part of people that are doing this trying to pretend that they have a business on the other hand if you say you know I have a gateway that actually can do a meaningful job of helping my customers optimize spend in other words I am creating value on top of my suppliers and it has some amount of stickiness and redeeming value that's a meaningful new category and so we look at inference for example in the context of can I offer my customers choice because we buy capacity in bulk both from open AI and from anthropic and we have the capacity to do things like run open weight models ourselves in that context inference becomes a little more interesting we also generally take the lens of it's important for us to understand what our strengths are our strength is as a data platform and inference as a component of a modern data platform absolutely makes sense to us and we also like to sell at the highest value creating point in other words my order of preference is always if I can convince a customer to use cocoa or co-work directly that's what I want them to be using if they say no all I want is model capacity from you I'm going to run my own harness yes we will do it if they say I want neither of those I just want the data platform and it can be a back into cloud we will do that as well somewhat more reluctantly it's important that you have your Maslow hierarchy of what where you're creating value and acting according to that and Brian and I are super aligned on what are the business outcomes that we want to drive let's say if cocoa adoption were to go up massively and it has an impact on our gross margin I'm happy to come and explain that to you all day long that's not and you know that's not an issue because it will drive a meaningful acceleration in our overall business and I can also tell you as we grow in scale as we do these things we get better at optimizing we get better at running open source models which will have much better margin we obviously buy a bigger quantity from the suppliers like we do with AWS and the six billion dollar contract which gives us better economics there are good answers to things like gross margin but it needs to make strategic sense what I have little appetite for is being a blind reseller of someone else's intelligence.

Brian Robins, CFO

100%. I think the analogy is what we do with the hyperscalers where we put our software on top of them and basically deliver a value added service that has good ROI for our customers. And that's really key. From a gross margin perspective, we have a lot of control over that. The hyperscalers is another, we announced I believe it was last quarter a big deal with AWS. We constantly work with our hyperscalers scalers to do stuff better, faster, cheaper. And we'll continue to do that as it relates to inference. When we launch new products, the number one thing we want to do is make incredible products that people will adopt, get value out of, and will drive revenue. And then we have demonstrated that we can actually show leverage in that once we get economies of scale and a number of customers on that um and so that's on the gross margin side regardless of that we're very committed to getting operating leverage in the model overall and that's what we guided to for the year and so the framework that we do go do our gross margin and we model you know we have very accurate models internally is based on the uplift that we've seen their ai products which is phenomenal and we like that and that's what we guide to for the rest of the year but we're confident that we can actually continue to get leverage in the overall model and do things around gross margin.

Gabriela Borges, Analyst — Goldman Sachs

I think this is an interesting thread to pull on just for two more minutes here. So let's fast forward and imagine that this time this year, Cocoa, we think, is a home run. And Brian is coming on the earnings call, and gross margin is not where the street model because Cocoa was fantastic. Talk to us a little bit about the guardrail on Cocoa gross margin, and Shrita, you sort of alluded to it there. You can explain this holistically as part of a much larger value proposition.

Brian Robins, CFO

Well, I would say first is, you know, we are a consumption business, and so it does take time to ramp. We also know, although we're bringing that down, and we also build models to understand what this consumption is going to be. And so it's really, Shredar and I don't want to surprise folks. And so if we were seeing that massive COCO adoption beyond what we're already seeing, we would have the ability to communicate that to you within a quarter or two to manage that.

Gabriela Borges, Analyst — Goldman Sachs

I want to ask a technical question on agents. So, Sridhar, there is a school of thought that the systems and architectures of today are not going to scale for real-time agents because agents have so much more volume, for lack of a better word. Talk to us a little bit about how you would address that concern if investors say, well, Snowflake was founded X number of years ago and is designed to scale for humans, not for agent queries.

Sridhar Ramaswamy, CEO

There's a little bit of a memeing and attempted category creation by the folks that say things like this, but 100%. there is some there is richer data that comes from agents and things like trajectory analysis for all kinds of purposes the good part is how do you make your team more efficient the bad part is is there someone in the company that's actually doing research on bio weapons like as a CEO you really want to stop that very quickly and so there's the the good and bad aspects of just needing to make sure that you do better with that but in all of this the overall criticism that we have not addressed super low latency data well is very legit I'm a big fan of like laying it bluntly to my team and accepting things when we need to do better I said this to you folks I think it was two years ago at what we had done in machine learning and notebooks it was not up to far fast forward to now you're not going to hear that from any of our customers not only is the offering really good we have also thanks to technology like Cocoa massively accelerated the process of migrating let's say from whatever set of notebooks that you have on to snowflake or being able to create not one but dozens of machine learning models as part of an experiment that you are running on making sure that we deal with data that say has 500 milliseconds or less of freshness requirement is not something that we do really well right now there's a team that's actively at work on this it basically comes down to things like what are the trade-offs that you want to make in terms of cost and efficiency and also just like the querying speed that you want you've been putting into place things like interactive tables for much lower latency serving under a streaming solution has brought things like the freshness down to the two to three second range and there's active work underway to bring that further down to the 500 odd milliseconds at which point it's being an issue. It's an opportunity. It's a threat. We are well aware. We absolutely are working on it.

Gabriela Borges, Analyst — Goldman Sachs

I want to ask the switching cost question both ways, which is we've talked already about speed of migrations accelerating to Snowflake.

Sridhar Ramaswamy, CEO

We've also talked in the last year about things like standardization of data tables and data gravity becoming less grave, for lack of a better word and how do you think about the longer-term implications from switching costs potentially going down in the data infrastructure world I mean just bluntly I tell my team this I'll admit this to to you if migration into snowflake can be made a whole lot faster migration out of snowflake can be made a whole lot faster that's the world we live in and it applies to data platforms it applies potentially to consumer software it applies everywhere and that is something that we all have to understand and so you have to and then there are also broader industry trends like a lot of CDOs and CIOs simply saying I don't want my data data to be held hostage by anyone you don't grudge them you can't grudge them for saying that so we support open format we want to increasingly make it painless for our customers to deal with open format so we have now something called snowflake-managed iceberg tables, which is a fancy way of saying you can have your cake and eat it too, which is you can store data with snowflake, but have it be queryable in iceberg format by any other engine. And the place where we create value has to be further upstream. It has to be in, do we provide better governance? Do we provide better disaster recovery? Is it easier to create and run agents on top of snowflake? Do we provide a better observability solution? And so there's this whole stack of things on top of the data platform that is open that we have to be providing. And to a large extent for a lot of these, my attitude is bring it on. It's not that easy to create the platform that Snowflake is. If it were, the hyperscalers would have eaten our lunch like, you know, 10 years ago. It is hard to do. And I think AI actually accelerates what's possible with Snowflake. But I think the Snowflake of old, which used to hang on to a set of what it thought were inviolables that could never change, I think that company has also changed. This is a company that's much more attuned to where is the world of data going, where do we create value, what is strategic value that we could be creating in a way that's still faithful to what our customers want. We feel good about how we are positioned. Absolutely. What can migrate in can migrate out. You need to both be paranoid about that, but also seize the opportunity while you can.

Brian Robins, CFO

We really, really drive internally this customer-first obsession. And so people can come in and leave easily, but if you have a customer-first obsession and really focus on the business cases, outcomes, and ROI, one of the top 10 skills that we have is around cost optimization. And so we want people to be fully optimized. We want people to use the product. We want them to get value out of it. And so we're constantly going back. If we see an anomaly with a customer, will actually go alert them and say, hey, your bill is running higher than it's been before, or are these jobs that you meant to kick off or not? And so really being obsessed with a customer I think really is a key priority for us.

Gabriela Borges, Analyst — Goldman Sachs

Let's stay on the pricing implication here. So I think about architectural enhancements in Snowflake, like the Gen 2 instances, for instance. You've got this natural pricing deflation in your business, like any good technology business, and yet your role is to also abstract value and price one level above the core components of that so you can capture gross margin. Maybe, Brian, just tell us a little bit about how that philosophy is coming into play in 2026 with things like Gen 2.

Brian Robins, CFO

Yeah, I mean, part of the business is you've got to be better from a price performance perspective than the last generation was, and you always have to give your customers the ability to get more out of your product, and so we price that in, but we're seeing also that with volume and new jobs coming into the company. And so we carefully, as we go and price stuff, we carefully take that into consideration so there's not big step-downs in revenue, but we also want to get our customers to get the benefit and the value of these performance enhancements that we're doing on the platform.

Sridhar Ramaswamy, CEO

I'll perhaps add on a quote from one of my previous bosses and mentors. Revenue solves all known problems.

Gabriela Borges, Analyst — Goldman Sachs

Let's leave it there. Please join me in thanking Sridhar and Brian for their time.