Snowflake Inc. (SNOW) September 10, 2026 Conference Transcript

Okay. Thanks, everyone. I know people are piling in after the keynote. So, you know, got a couple seats up front, but I'm sure this will be a standing room session. Excited to kick off the afternoon with Snowflake. We have Brian Robbins, the CFO. Brian, we had a great dinner last night, and it's hard to believe it's only been a year or so since you've taken over. A lot has changed at Snowflake. Maybe just give us your top observations from the past year and how do you think about the opportunity ahead?

Yeah, absolutely. First and foremost, thanks for having us here today and thanks for everyone coming to see us. My two primary goals when I came into the company was really twofold. One, focus on growth and margin expansion and two, focus on the go-to-market at execution. And so in my career, I've spent most of my time with the CROs of the companies and have really focused on that go-to-market function. And so, you know, and I'm happy to say both of those have really played out throughout the year. You know, on the growth and margin expansion, really happy with the guidance that we gave, the quarter that we delivered, even the previous quarter. And we're doing that with increased operating leverage in the model. And so excited to see that. Sharita and I are very well aligned there and the whole executive team is. You're starting to see the investments that we made pay off in the go-to-market and also on the growth side. On the go-to-market side, JB Jonathan is our new CRO. He's doing an awesome job. He's been at the company for over 10 years, really highly regarded. It's been awesome to work with him because he grew up with Snowflake, basically, and knows the product really well. And so he's really pushing the discipline and changing the way the sales force is selling into our customers. So historically, when I got at the company, it was really a consultative sales approach. And they would go and sort of talk about what's your problem, how can we help you, and so forth. And now reps are actually using AI with synthetic data and actually deriving outcomes for the customers. So they're actually showing up with agents and models and so forth that actually help drive that use case. in that outcome. And so really super happy that those two things have played out. And two of my focuses I'll continue to focus on.

Okay. Awesome. And certainly the recent results have been very positive surprises to the market. Back to back reaccelerations, very rare in software at the scale, 5% plus beats, but it's also rare by Snowflake history. Clearly, investors are excited about it. We can see the bend in the growth curve. But I'm curious, as you kind of look at the business from probably an unlimited amount of metrics based on how much you can cut the data at Snowflake, what are some things that surprised you internally, whether it's verticals, new personas, different types of consumption patterns?

That's one advantage of being a data company. We actually measure everything within the company. And so just to comment on the results, and we'll talk about the question, you know, it's awesome to see what the Snowflakes have done and what they've delivered. A lot of hard work has gone into that throughout, you know, the entire employee base. And then, you know, also really appreciative of our customers. You know, when we, Sridhar and I host in all hands after every earnings call, and it was one of these things like, hey, this is great. Let's celebrate today. But like after today, like we have to worry about tomorrow and this quarter. And so there really is a sense of urgency within the company and a culture around customers first, delivery, product innovation, and so forth. On the second part of the question, remind me it was about...

Just as you look at all the different metrics and cuts of the data, like obviously investors, you can see this shit, but anything that you would flag and just stand out to you as you look at...

I guess it would be, of course, the metrics are awesome to look at and see what's happening. One, I guess, would be really the durability of the business itself. And so what we're seeing with all the AI initiatives that we have, we talk a lot about COCO, but there's co-work, there's AI functions, there's model training, there's AI gateway. It's the adoption of those and what people are doing with those tools to impact their businesses. And so the way that all of us are working today will dramatically change in the next year, two years, three years. And trying to actually embrace that agentic workforce and what that looks like and to see that in our customers and see how they're doing it, it's just been awesome. I guess the other thing that I touch on that's really been amazing is, when I got to Snowflake about a year ago, I personally did not use Snowflake that much. I don't know. I took SQL, I think, in college. It was a required class. But I didn't really have the ability to access the data like I have the ability to access the data now. And so I spend a lot of my time in Snowflake, primarily Coco, and can access any of the data. So historically, the way I would work is if I would see data, and one of our traits that everyone here in the room has is we can look at reams and reams of data and find one data point that doesn't make sense. and then typically we would go to someone and say can you give me more data on that now you can just talk to basically your computer through coco and basically get into the data and understand what's going on and then it's integrated with our acquisition that we did with mcp connectivity into gmail calendar slack all the other applications i use i use that as a harness to work out of and the fact that i'm using it so much and we've implemented so much snowflake on Snow, I talked to probably three to five CFOs a week, either existing customers or potential customers. And the sense of urgency around what you can do with your data at different personas has been really amazing.

Yeah. Yeah. No, that's great to hear. And I know you've talked about vast, vast majority of the finance org on Coco and just all the efficiency that that's gained. And, you know, one of the questions we often get from investors, and I know you've only been at Snowflake a year, so this might be a little unfair of a question. But if we go back to past, you know, cycles, right, where we did see larger beats and growth rates were elevated, there was this wave of optimization. And I know that's probably, you know, very recent memory for a lot of folks that are still at Snowflake. What gives you the confidence that this acceleration is durable and we're not going to face this huge wave of, you know, optimization like we saw maybe five years ago as the digital natives kind of lost some momentum?

Yeah, you know, it's a good question. You know, and you can ask me any question. I got my colleague Catherine here. And so anything I get in trouble with, she'll help me out. But, you know, from the, you know, when I look at the data and sort of understand the past and sort of what's going forward, we're well past the experimental phase with, you know, COCO and AI. And really seeing the power of what this does within our customer base gives me the confidence in forecasting it and putting guidance. You know, when you have sort of a new tool and a lot of people adopt it and use it, that's great. But what you really have to ensure is that you're driving positive business outcomes and there's an ROI on that. You know, one of the things with a consumption model is you get to charge like every day when it gets consumed. But if you're consuming for the wrong things or they aren't seeing an ROI, that's like bad for the business. Like that's like not sustainable. One of the things that we actually have, one of the things that we have that is awesome is we have a skill within Cocoa to do cost optimization. And it's one of the top 10 skills that's used. And so we actually encourage and want our customers to do optimization. We encourage and want our customers to use Cocoa, but we don't want them to do it in an unhealthy way. And so part of the sales execution and excellence that I talked about with JV and the sales team is really developing those use cases and selling those outcomes. And I think that's critically important for stability in the business. And that helps us put that into guidance with durability and understanding.

Yeah, and maybe we can stick on guidance for a bit because I know there's a lot of factors. Your favorite, right? A lot of factors, a lot of time, effort, heart that goes into that, right? But how do you approach it? I mean, you're seeing kind of unprecedented levels of adoption, new use cases every day, and new products launch, right? I mean, the innovation velocity. So what, in simplest terms as possible, like, what are you assuming in the guide now that maybe you didn't three months ago, whether it's new products, level of consumption, just to kind of help frame how you're guiding the things?

Yeah, let's, before we jump in, let's talk a little bit just about guidance itself. and so just want to make sure there's no change in guidance philosophy we do it the same way when when we look at guidance we look at sort of the core which we have a ton of information on and we actually forecast that literally every night we have um there's an awesome team back at snowflake they the team's been there roughly about eight years there are a bunch of data scientists and they they forecast by customer and by product line literally every night so the pipelines run for four hours at 5 a.m. every morning, I get an extremely detailed forecast of what's happening within the business. And so with the core, you know, we have tons of data. We've done that for a while. Our degree of accuracy is very high there. And with AI and some of the new products, you know, we don't have as much observed data. And so we're going off of what we know you know serve at the time um that same team as well as another team builds detailed product launch model source and so we have all the products over the course of snowflake we have all the curves and the trajectory of what those products have done and then we apply the pattern recognition behaviors to those based on what we're observing and so with coco only being out two quarters you know the first quarter that we did it we didn't include it because we didn't have any their behavior now we're able to um you know the the next four we're able to but you know we don't want to put in the initial sort of the you know small numbers but really really high growth percentages and so we took a haircut to that but now that we're two quarters in we have more data we feel like we have a better accuracy in forecasting that then we have a whole bunch of new products that you know obviously are new so we don't have a lot of observed data and so we don't put a lot behind those right now.

Yeah. And on those new products, I mean, what are kind of the top two or three new products that are now out there that you're most excited about or customers are seeing kind of initial traction with?

Absolutely. Cocoa Sibling is called Co-Work. And so Co-Work has over 5,000 accounts. You know, Co-Work is what I'll call data with rails around it's like certified by the data scientists and so we go into co-work and ask questions there's no hallucination the data is correct you can actually roll that out to a lot of people so love that um you know the ai functions we're seeing uh ai gateways super early uh but you know one of the things that we're seeing with our customer base is you know their commitments to some of the large foundational models because new models are coming out on a pretty frequent basis they want to be able to have model choice and so one of the things that we're able to do is people make a snowflake commitment for cocoa and consumption and be able to use the right model for sort of the right question or the right activity the right query to basically optimize the cost they're paying for that and so you don't want to use the most advanced most technical most expensive model for a very very basic question and so you'll use maybe an open source model or model that costs much less.

Right, right. Makes sense. One of the other questions we get just in terms of some of the recent performance is this sort of distinction between AI driven and the core, right? And I think it gets a little confusing because AI can benefit the core. Like new use cases, you need more data. But can you just sort of talk about those two dynamics and how do you kind of see the growth of the core business trending just given these new use cases that are coming on top of it?

Yeah, absolutely. When we put our revenue together, there's no, and I know a number of companies do attribution to saying AI revenues this and maybe they're selling a bundle and they have to, for accounting purposes, they have to break it out. Ours is down to the SKU level. And so we have a series of products that are AI related. And so when we talk about AI and the performance, it's based on those SKUs. And then the core is the core business that data warehousing, storage, analytics, ingestion, what you know is Snowflake as a whole. And so one of the things that we're seeing that is extremely encouraging and really goes to the durability of the business is we're seeing that when people adopt our AI products, primarily Cocoa, because we have the most data around Cocoa. They're actually consuming more of the core. And so it may be more personas. And so you're reaching more people within a business. So typically pre the Coco and all the AI functions, you would basically interact with Snowflake through your data team who would actually write the SQL queries. Now, anybody within the business can get access. And we don't charge, like Coco's not, we don't charge for it. You just get it being a Snowflake customer. And then the charge is the consumption that you actually draw in using the product. And so we see more personas, and then we're seeing migrations go faster, and so we're seeing more data come in relative to migrations. So there's a whole bunch of different things that AI is doing that's driving strength and acceleration in the core.

Yeah, got it. And presumably with the acceleration implied in the guide, you're kind of seeing those trends continue on a go-forward basis. another topic that you led off with in terms of your priorities was margins, right? And I guess, how do you think about sort of trade-offs with higher AI revenue, right? Gross margins were lowered a bit last quarter in terms of the full-year target. Just give us a sense of how you think about that going forward as Snowflake becomes a greater AI business?

Absolutely. I guess the first thing I'll say is we're in such an awesome market today. There's so much opportunity and it's changing so rapidly. And there's just so much opportunity out there. And the TAM, because of these things that we're doing, is expanding very, very rapidly. And so So with that, you know, Stradar is very committed to revenue growth and, you know, meeting our customers where they're at, giving them tools, helping them get value out of their data through AI and other methods. And so, you know, the number one thing from a company perspective is, you know, we want to capture that market share. And so growth is extremely important. You see in our guidance for the full year, we raise it from 31% year-over-year growth to 36% year-over-year growth. And so that's a pretty significant step up off of a prior quarter where we had another big increase. But we've done that with increasing operating leverage in the business. And so what we are very committed to is increasing operating leverage in the business. For those of you who weren't at Investor Day, we committed to being GAAP profitable in fourth quarter of next year. And so, you know, slightly over a year out. And so we're seeing a really big, you know, we put a plan around stock-based compensation. You're seeing a really big decline there. You're seeing us hold gross margins, you know, with the increased revenue that you see. We got 74% non-gap product gross margins. And you're seeing the strong cash flow generation. And so we're doing that with less people around the enterprise. One of the things I talked about on earnings, if you look at sort of year-to-date hiring for first and second quarter, this year versus last year, we added roughly 330 people this year. Last year, we added about 950 people. Of the 330 this year that we added, 180-ish of those, more or less, came from the Observe acquisition. And so the amount of people that we're adding with the acceleration of revenue, I think, is really a testament of how times are changing. On gross margins specifically, the company's done a really good job over the years of basically getting leverage and scale with our providers once we sort of reach a certain threshold. And so as we launch all these new AI products, AI products naturally have a lower gross margin than our core business. The good news is it does drive our core business, so that's helping out. But we feel that there are things that we can do over time to maintain a strong gross margin.

Yeah, and you talked about on the operating margin line and particularly the people side of the business, right, having to hire significantly less despite this growth acceleration And certainly was evident to us, you know, at Investor Day, just how much internally Snowflake has kind of transformed on this AI organization, certainly across product velocity, you know, your finance organization as well. What are like some of the biggest efficiencies that you've seen through that transformation? And do you kind of feel like this is the new normal of like very, very minimal headcount growth, even if growth were to continue to accelerate from here?

Yeah, you know, efficiencies are happening all over the business. You know, if you start at the top of the P&L on revenue, you know, we're seeing efficiencies in the sales organization. We actually, you know, have a model called Raven, and people can go in and speak to Raven really about anything. And so, you know, for instance, if I got the user list of who's here attending in this, I could easily download it into Raven and say how much ARR is sitting in the room for financial services as a big vertical force. And so, and it would tell me basically by customer, you know, what everybody's spending and who's not customers. And so the power to do that is, is like, I could never do that, right? like it would basically i'd have to get the list i've just sent it to an fpna analyst it would take a while they would go do all this stuff but you know with these models you can actually connect all this different data structured unstructured and literally get it at your fingertips and going back to the cfos that i talked to and the ceos that sridhar talked to you that's why they're so passionate about like i need to get this yesterday and get it in my hands and so from the sales side, you know, we're seeing it on prospecting, how they're putting deals together and so forth. And so we have not hired as much in sales and seen the productivity per rep go up dramatically this year. And that's within the sales organization. And so, you know, I know folks like yourself would go and scrape the internet for open racks and try to see how much people are hiring. And that would be an indication of growth. Like, unfortunately, you can no longer do that. On the R&D side, with relatively flat declining headcount, we're getting increased productivity on lines of code produced at an astonishing rate. And so what we're doing is one of the things that we're doing to get Guy profitable was a big component of that was stock based compensation. And what we're doing is we're hiring a different type of person that can actually be an engineer versus what we would historically hire. So historically, you'd have to hire someone with, you know, eight to 10 years of experience, really senior, maybe had a management role in the past. And now you can hire someone one to two years out of college who really is AI pilled, that his vibe coded, can use cocoa and so forth. And so we're seeing a dramatic difference in the two of them on the productivity. If you go into the finance organization, we have probably 150 50 different use cases. I say probably because they're developing them every day. So it's more than that on how we're using Snowflake Gone Snow on doing automation. And so it's sales and marketing, the same thing. You know, HR, we have an HR skill that can give you the health of your organization and can tell you everything you want to know about your organization and people to check on, people's stats and how much they're using AI tools, like a whole bunch of different stuff. And so the point of all this is, you know, we're seeing efficiencies and you can tell by headcount, but I really think we're just getting started. You know, I think the efficiencies that, you know, I think of the curve of adoption and proving out the efficiencies. We're in the early beginning stages of that. I talk a lot about AI being a human transformation more than a technology transformation. And so really getting individuals to understand what the art of the possible is is really really important and so i meet every week uh one-on-one with my direct and someone from my data science team a data you know senior data analyst manager to talk about what they're doing to become ai native and how they're changing their organization it's just literally every week a one-on-one just on ai in their function internal audit investor relations you know accounting fpna tax deal desk because it's that important and you know it's amazing to see the light bulbs go off when you talk about the art of possible and so you have to give them this north star of what they need to shoot for on what they can get to from the art of possible so we're building a lot today we're seeing efficiencies but i don't think we're seeing as much efficiency that you'll see over time once we get some of this stuff fully deployed

Yeah, well, that sounds really exciting and certainly a kind of a new lead generation opportunity for you if you're meeting with CFOs every day and showing them what can be accomplished.

Um, I guess, as you think about, you mentioned the, um, the North star, uh, and how important that is, like, where do you, you know, at a high level, where, where do you and, and Sridhar view the, uh, the potential of this business? I mean, there's, there's certainly been targets that have been put out there, uh, years ago growth, growth is on, on the upswing, but how do you, how do you kind of characterize that North Star goal to your group of Snowflake, your Snowflake employees every day to keep them motivated?

You know, the market is, like I said, rapidly changing. And one of the things, I love many things about Snowflake, but one of the things I love is we are spending millions and millions of dollars, tens of millions of dollars, re-educating and retraining our employee base on what it is like to work in an ai environment and we're really driving that and so i mentor a number of people and they'll come to me and talk to me about careers and maybe taking a cfo role and so forth and you know if you're in the job market today like it has to be one of the most terrifying things because there's there's a lot of companies that just won't be here in two three four years um and so what i tell them the most important thing is to get with a company is ai forward they want to make sure your ai filled and they're going to invest a lot of money in you and um you know the way i used i've been doing this for about 30 years and the way i used to work won't work going forward it just it won't work and so um i'm really bought into it and really spent a lot of time on it because i think it's i think it's critically important and so from a snowflake perspective um people are extremely excited because you know all the customer stories that they're hearing, the impact they're making around the world when AstraZeneca comes and talks and they've done case studies and press releases with us and so forth. And they'll come talk at Summit or whatever. And they're like, you, Snowflake, are saving people's lives. We've been able to X, Y, and Z because we've implemented Snowflake and are far along on that. They're getting drugs out to trial faster. They're doing it more economically. And it's just awesome to see those results and that's in life sciences and then you go to supply chain you see the same thing you go to government pubsec and you see the same thing and so it's super exciting um and within my organization there's five or six people who talk to customers on a regular basis and that happens around the company and then people bring those stories back and they talk about that um you know obviously the earnings that we're posting is really awesome but for sure and i we want to basically create a set of tools and the ability to access your data to be able to drive your business more efficiently so you know more about your business and you know we're in you know we're at the center of ai and doing doing a just an awesome job at that and you know the key for us to continue to be successful is product velocity um what you did yesterday doesn't matter for tomorrow. And so we need to develop the next COCO, the next COCO, get deeper penetration within the account, and also sales execution.

Yeah, that makes sense. Brian, as a CFO, you probably are involved with the renewals of a lot of third-party software contracts at Snowflake. And certainly there's been a lot of concern in the market around traditional SaaS businesses. And we've seen them kind of make moves to kind of look more like databases in some ways with UI layers going to AI labs and everything. how do you kind of see this this playing out both from what you're doing with your third-party software contracts putting more stuff into snowflake and then the opportunity for you to kind of be more of a operational database in some of those use cases for your customers

yeah great question so let me unpack that you from you know so i procurement sits under me as well and and so i get to see all the deal that sort of come through the pipeline and

because things are changing so rapidly i am very hesitant to do three-year deals and so you know i won't save money but i won't get locked into a long-term commitment and so you know i'll i'll basically sign one-year deals not saying i won't sign three-year deals there's some software that is critical to what we're doing that will be there and you can tell it will be there in two to three years or we've talked to them about their roadmap their ai pill they're changing the way they're working um and so some we will do some three-year deals but you know that the standard is a one-year deal um you know where that's changed a little because historically you want to commit as much as you can for as long as you can to get the biggest discount you can um and i'm just not you know because things are changing so rapidly i'm just not you know i can't in my mind i just have a hard time wrapping my mind around that uh so we're actually doing um you know lower deals from a um from a you know data coming into snowflake and then other companies trying to be a database or be a database site you know the thing about snowflake that is incredible is you know we are an open system we have the iceberg tables where you know we're encouraging you to you can query your data from any anywhere anyhow or whatever you know it's our um you know we have to create great products like coco to incentivize you to use us um one of the things around um you know that we talk a lot about internally is you know it's customers first if you don't make a great experience for your customer um we talk about it's really easier to migrate into Snowflake because of all these tools. It's just as easy to migrate out of Snowflake. And so let's say the reverse of it too, right? And so we have to create those great customer experiences to keep them within Snowflake and to give them the ROI of doing that. And since we don't run, we aren't an HR application, we aren't a CRM, we don't run all these various components. Like a lot of people want to put all their data in Snowflake so then they can use tools is to actually be able to understand more about their business. And so I'm very encouraged with how things are going and what we're seeing from a business momentum perspective with people putting data into Snowflake.

Yeah. One of the questions we often get just on the competitive landscape is what do we make of the Frontier Labs, right? Obviously, you have a coopetition dynamic with the hyperscalers that you're used to, both partners and competitors. How do you see the Frontier Labs? Are they in a similar boat as the hyperscalers, or do you view them differently?

Yeah, I think, you know, I've talked a lot today about sort of the changing business environment. You know, we have great partnerships with the hyperscalers. We also compete with them in some way as well. And so, but, you know, I talked to, you know, the account, the CFO of AWS, John, on a very frequent basis. I talked to the folks at Microsoft and the folks at GCP on a regular basis as well. And so we have a very good relationship there, you know, and, you know, and they're using us as well to sell more workloads. And so they're, you know, in some cases they're giving quarter relief to their team to do that and so forth. And so we have a good working relationship there. And same thing with the large foundational models. You know, we've, you know, just did our summit that we recently had. We had the co-founder of Anthropic up on stage with Stradar talking about the partnership. Now we're working together. We work very closely with OpenAI. Christian talked a little bit about SpaceX and Grok. And so we're working with all of them. And so I think you said it right, you know, there's a very healthy, stable partnership, but, you know, there's also some form of competition as well.

Yeah. And maybe in the closing minute or two here, Brian, if you're sitting back up on this stage, you're certainly welcome back next year. And growth rates have meaningfully accelerated once again beyond where anyone's thinking of. What would you say are kind of the two or three main reasons why that happened? And anything else you just want to leave the audience with before we wrap up?

You know, I think it's, you know, Catherine and I aren't doing our jobs if we aren't communicating to you on a regular basis about the business and the driving factors of where we're going. And so there shouldn't be any surprises. And I think it really is the durability of the business as it relates to AI, you know, the ability to do migrations quicker, to get more personas, you know, to basically get deeper within these accounts and to really show them, you know, what can happen. So I don't view from now to next year, it's, you know, given a forecast in these markets is just absolutely crazy. And so we're trying to execute every single quarter, but I think you'll see more of the same. We're developing a lot of AI products and features really with the goal of driving consumption and for getting people to put more data within Snowflake. And so that's really the goal of the company in this AI era that we're in.

Awesome. Well, Brian, really appreciate you coming to the city conference. Thanks, everyone, for packing the room. It's a great discussion. Thanks so much.