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Ron Gabrisko, Databricks
In this theCUBE + NYSE Wired: Mixture of Experts segment from the New York Stock Exchange, theCUBE’s John Furrier sits down with Raj Verma, CEO of SingleStore, to unpack how the intersection of technology and finance is shaping enterprise strategy. Verma shares why SingleStore is “on course” for the public markets, reflects on brand-building through the company’s partnership with golf Hall of Famer Padraig Harrington and connects that ethos to how SingleStore helps organizations fix struggling data “swings.” The discussion zeroes in on what’s next as Wall Street watches the AI infrastructure buildout: after chips and systems, the software and data layers set the pace for value creation.
Verma outlines why enterprises must modernize “brown” data estates into “green” ones to safely bring corporate context, governance and compliance into LLM workflows via RAG – and why commoditized data-at-rest puts the advantage at the query layer that unifies data in motion with data at rest. He predicts agentic AI will gain reasoning capabilities in roughly 18 months, cites industry indicators like Google reporting ~25% of its software now built by AI and argues that high switching costs will give way to disruption as buyers reassess legacy vendors. The conversation closes with concrete momentum: ~33% YoY growth, ARR in the ~$135M range, gross dollar retention ~98%, cloud NDR ~130, ~50% of business now in the cloud, landing ~3 new customers per day, a path to cash-flow breakeven in the next two quarters and a teaser for AI-related announcements in the next two months. Listeners will find notable stats, real-world use cases and forward-looking views on how databases power reliable AI at enterprise scale.
play_circle_outlineDatabricks: Revolutionizing the Data Industry with Unprecedented Growth and Valuation Insights from CRO Ron
replyShare Clip
play_circle_outlineMaximizing Competitive Edge: Leveraging AI on Proprietary Data and Transitioning from Data Lakes to Generative Applications Across Industries
replyShare Clip
play_circle_outlineThe shift in focus from cost savings to revenue growth with AI.
replyShare Clip
play_circle_outlineDatabricks’ internal use of AI for predicting revenue and account management.
>> Welcome back around to theCUBE here at the theCUBE's NYSE East Coast Studios and access point, part of our NYSE Wired communities and open access network, bringing leaders together, so a mixture of experts. We talk about the leaders, where the experts where all the reasoning happens here on theCUBE. We have the CRO from Databricks here. Ron, great to see you. Thanks for coming in.
Ron Gabrisko
>> Thanks for having me. Excited to be here.
John Furrier
>> Chief Revenue Officer of Databricks. Well, first of all, your valuation's awesome. Congratulations on the-
Ron Gabrisko
>> Thank you....
John Furrier
>> monster valuation and the continued growth. We've been following Databricks from day one, going back to the old Hadoop didn't work, Spark comes, data lakes come in, lakehouse, and then just the adoption of having your data act together really kind of sets the table for now what is the dream scenario for that, which is generative AI and-
Ron Gabrisko
>> Really....
John Furrier
>> and all the software and open-source developers leveraging this infrastructure. You guys have been really successful, and also still in a great position, bringing in all kinds of new algorithms, extracting away complexities, making it easier. Ali was on yesterday detailing that out. Quite a run.
Ron Gabrisko
>> Yeah. Thank you. Yeah. No, absolutely incredible. I mean, we're just getting started.
John Furrier
>> How's the revenue numbers?
Ron Gabrisko
>> Doing well. We're doing all right.
John Furrier
>> What's the forecast?
Ron Gabrisko
>> Exactly.
John Furrier
>> Are you guys looking good from, as they say, middle of the fairway in golf?
Ron Gabrisko
>> Yep.
John Furrier
>> You guys have been using AI internally. One of those top stories that I wanted to get in with you is how Databricks has been driving innovation on the data side. Obviously, the Cal pedigree. Now, they've got a great computer science bench, a lot of schools coming together, so the tech, the vision, the strategy all working.
Ron Gabrisko
>> Yep.
John Furrier
>> Now, customers are using it, scaling up with the data lakes, doing a lot more. What are the top things are you seeing from your customers right now in terms of that kind of next-level value from the data lakes as they start to think through how to have a generational platform for generative AI?
Ron Gabrisko
>> I mean, if you think about it, every single one of these companies will become a data and AI company. How they'll compete, win, lose in the market is how they apply AI to their proprietary data, and so it's in every single industry. Like healthcare, we've helped companies discover new cancer drugs, all the cancer treatment stuff. Agents read all your medical records to try to discover drugs for clinical trials, financial services for fraud, I mean, it's every single industry, but a big part of it is how do you apply AI to proprietary data to have a competitive advantage?
John Furrier
>> We're seeing the on-prem adoption with AI factories and other large-scale systems because there's a fear of putting those crown jewels into the public models. The emergence of, and you guys talked about this last year at Data and AI Summit, which is there's a power law of smaller models. They work together and the need for customers to have their own so they can actually apply that to agents.
Ron Gabrisko
>> Yeah, yeah, so I mean, we're entirely in the cloud, so most of the modern data stacks we'll move to the cloud, but the biggest part is we're not doing general intelligence. A lot of the frontier models, if you want to know how did World War II play out, they've been trained on all the internet data. The proprietary data that's inside of companies, applying AI to that to make more strategic or better decisions, or even automate processes, that's how AI gets applied to data. We have partnerships with all the major frontier models, OpenAI, Anthropic, Gemini, Lama, et cetera, and how you can kind of do governance, make sure that your data's secure, that it's not using your data, that's really important for these companies.
John Furrier
>> When they look at those models, they're thinking as a developer perspective, they're trying to build solutions.
Ron Gabrisko
>> Yeah, totally.
John Furrier
>> What's the biggest use case that you guys see in the enterprise right now that's got the most traction, momentum?
Ron Gabrisko
>> I mean, it's all across the board. Like I said, there's massive, and it kind of depends on the industry. Lots of people are trying to automate call centers. I mean, that's kind of bread and butter. Lots of agents doing that. I saw some really cool developments in retail. so they were measuring shrinkage on food shrinkage and spoilage and things of that nature. They had agents to do repricing, agents to do promotions. Just really cool in retail. Lots of sports stuff. The new Fox Sports app, Cleatus, I don't know if you're a sports fan, but that's all AI-driven by Databricks, so .
John Furrier
>> Yeah, people are using the AI agents to make their picks on their fantasy-
Ron Gabrisko
>> Exactly....
John Furrier
>> you know?
Ron Gabrisko
>> Exactly. Mine's not doing too good, but-
John Furrier
>> I'm not going to lie. I definitely when I'm getting my picks in, I didn't put time to prep. I definitely I have gone to the-
Ron Gabrisko
>> Exactly....
John Furrier
>> cheat sheet.
Ron Gabrisko
>> .
John Furrier
>> It's right there. ESPN, they're all publishing their content. I Mean, why not grab it?
Ron Gabrisko
>> Yeah, exactly.
John Furrier
>> All right, as CRO, I want to ask you kind of the revenue question because this comes up a lot on all of our AI series, whether it's AI Leaders, Robotics, Factory, Mixture of Experts, the conversation has shifted over the past year from cost savings. Well, it's always been kind of like, "Oh, you get some cost savings and revenue bump," but no one could really articulate that. Now, it's kind of shifted towards revenue.
Ron Gabrisko
>> Yeah, totally.
John Furrier
>> Knowing Databricks' pedigree technical company, I'm sure you're under pressure to get the AI going for you.
Ron Gabrisko
>> Yeah, for sure.
John Furrier
>> What are you guys doing on the revenue side of CRO? Can you share some of your thoughts around how you're using agents or AI for your team?
Ron Gabrisko
>> Yeah, absolutely. I mean, first of all, as an AI company, we've adopted AI machine learning from the beginning. I would say we were doing AI before AI was cool, and our entire business is built on Databricks. We call it Databricks on Databricks. We have our own lakehouse, we have all our data in there. I can predict our revenue within kind of 1 to 3% down to each customer. I know which customers are going to churn. We have next best action on which solutions we should be selling customers. We automate a lot of the account plans. We're automating some of the account followup like lead followup, things of that nature, so we apply it literally across the business.
John Furrier
>> You use it for qualifying, too, as well?
Ron Gabrisko
>> Yeah, totally, like all in our marketing. Which campaigns should we run? How should we articulate specific email campaigns? Or-
John Furrier
>> All right, what's the-...
Ron Gabrisko
>> you know....
John Furrier
>> coolest thing that's popped out of this that you could share? A story or some bluebird deal came in or why we saved the company from going-
Ron Gabrisko
>> Oh....
John Furrier
>> somewhere else? There's got to be some stories-
Ron Gabrisko
>> I mean-...
John Furrier
>> you know?...
Ron Gabrisko
>> literally, if you look at how we can predict our revenue, like holidays, all that kind of stuff, it follows the predictive line really, really close. If it bumps off of it, we're like, "Why did it?" They're like, "Oh, they had some random holiday in this country that we didn't. It was on a Saturday last year and this year it fell on a Friday." Literally it's that kind of precision. It's pretty cool.
John Furrier
>> Precision helps you guys do what? Adjust the sales tactics, your Biz Dev components?
Ron Gabrisko
>> Again, you're trying to grow the revenue as fast as possible, so knowing what's making that happen. Is it certain AI trends? A lot of the things we're selling into agents, we just crossed a billion dollars in AI revenue. Or is it some of our core data warehousing technology? We'll kind of see all those trends of different products with different customers. We'll know like, "Oh, this customer looks like they're having some trouble. Let's lean in more there with some of our executives or some of our technical folks." So-
John Furrier
>> I was kind of hinting with this yesterday with Ali Ghodsi, who came in yesterday. You guys pretty much nailed the technical buyer over the early years.
Ron Gabrisko
>> Yeah.
John Furrier
>> Data lake, people loved it, saved them money. Knocked down their cloud bill, make it more efficient. You guys went serverless. Okay, that changed the game there, so a lot of technical customers love Databricks.
Ron Gabrisko
>> Yeah, totally.
John Furrier
>> Okay, so now bridge that with the business outcome focus because what we're hearing now from Ali and the team is look at there's real work to be done. Let's just get that done and get the proof points out there. That's a business outcome-
Ron Gabrisko
>> Totally...
John Furrier
>> thinking. Take me through the mindset of how your emotions have changed or your customer behavior. Now you're crossing over into the business realm of-
Ron Gabrisko
>> Totally....
John Furrier
>> what's the value? Can I quantify it?
Ron Gabrisko
>> Yep. Yeah, so I mean, you think about like now AI is a CEO-level discussion,. It's not like a chief data officer. Certainly it's part of the chief data officer and CIO, but it's a CEO. It's like, "How are we leveraging Ai to transform our business so that we don't get disrupted? How do we provide better customer service?" All those things, so it's not about like, "Hey, let's just take out some legacy costs." It's literally like, "How do we transform and offer new services to customers? How do we provide better service to customers? How do we launch new products? How do we open up new regions?" All of that's like more strategic of, "How do I grow my business?" As a strategic advisor to a lot of those customers, we need to know. We need to know more about their business and so how it's going to impact their business and help them with that.
John Furrier
>> You know, last year I noticed Databricks had a big presence at NRF-
Ron Gabrisko
>> Yep....
John Furrier
>> and as did Salesforce and others. I'm like, well, we're going to cover it again this year here out of our studio, but clearly that's an Ai show. MWC, we knew that was an AI show-
Ron Gabrisko
>> Totally....
John Furrier
>> years ago.
Ron Gabrisko
>> Totally.
John Furrier
>> Supercomputing, that was HPC, High-Performance Computing Show now like four years ago, converted to full AI. That's a semiconductor kind of level. Let's take retail for instance. AI can change the go-to-market for any company. That's what you do. You're handling the go-to-market for Databricks.
Ron Gabrisko
>> Yep.
John Furrier
>> What lessons have you guys learned for that practitioner-
Ron Gabrisko
>> Totally....
John Furrier
>> that's saying, "Hey, look, I'm going to get the data set up, my tech team's on it, we're using Databricks?" What's the next chain? Hat's the impact to the executive who's bleeding the go-to-market?
Ron Gabrisko
>> I mean, it's real-time applications for how they run their business, and it goes all the way down to like the distributor or sales rep. If I'm running kind of sales for, say, a soft drink or Pepsi or some of the beer distributors, they're covering these stores, it'll literally tell them like, "Hey, you need to sell more of this kind of coffee," or, "You should run this promotion," or, "You should be doing this." Take a picture display and it'll actually tell you, recommend, "No, put this on the top shelf." Those kind of things, it's pretty amazing. Even down at that level, it's like a cockpit for the distributor or salesperson. Then, if you look at it as an executive, we literally created an application. Like I said, it was the intelligent store and it'll show like, "Okay, this particular store is doing really well. This store is not doing so well. What are the differences? Is it demographics? Are they running different promotions? Do they have a different product mix?" It's actually making real-time recommendations to help you improve your business.
John Furrier
>> A lot of predictive?
Ron Gabrisko
>> A lot of predictions. Exactly.
John Furrier
>> What on the generative AI side, on the customer? Are they having any changes on how-
Ron Gabrisko
>> Totally....
John Furrier
>> their relationship with the customer changes?
Ron Gabrisko
>> I mean, think about it. Now, you're able to talk to your data, so in terms of customer service on agents, any business, you have an issue, you're trying to get service on your vehicle or yo have a return with a retailer, all of that is being automated with agents. It's going to pull your records, your customer service. It's all going to try to automate that. It's going to improve the human service. In some cases it may replace the human service, but in most cases it's like gather all the information and still keep the human element of how you do customer service, so...
John Furrier
>> What's it like being the CRO of Databricks the past decade? I mean, I think you guys are on the Series K. I mean, we might run out of-
Ron Gabrisko
>> We're running out of letters....
John Furrier
>> we might run out of an alphabet. Might go to like hexadecimal or some sort of numeric financing system.
Ron Gabrisko
>> Yeah, exactly.
John Furrier
>> I mean, quite a rocket ship.
Ron Gabrisko
>> It's so fun.
John Furrier
>> What's been the biggest learnings for you at CRO? I mean, you've navigated massive growth while technology change has been happening.
Ron Gabrisko
>> Well, I mean, first of all, we have seven... Should I just keep going?
John Furrier
>> Yeah, it's still going. Yeah-
Ron Gabrisko
>> Yeah, okay....
John Furrier
>> it's an option bell.
Ron Gabrisko
>> All right, no worries.
John Furrier
>> Option market's-
Ron Gabrisko
>> You know-...
John Furrier
>> now closed....
Ron Gabrisko
>> we have seven PhD founders that created one of the greatest pieces of software in the world and just wanted to change the world. They literally gave it away for free, and how we built the business, and we built it together, was we focused a lot on the customer. How do we provide value to the customer? At each phase of the company, you have to kind of change, so as a leader in how I've built the go-to-market trade, I've also had to change. Kind of the zero to 20 or 50 million, it's product-market fit. Hundred million's like how you scale, build a playbook. A billion dollars, much larger scale where you're having to replicate things and grow internationally and grow with partners. Now, we're on hyperscale multiple billions, and so each phase is a little bit different, and so-
John Furrier
>> Which one's your favorite?
Ron Gabrisko
>> Oh, they're all different and they've all been-
John Furrier
>> It's like kids. They're great when they're in elementary school. They get just as hard when they go to the next level-
Ron Gabrisko
>> Yeah, exactly....
John Furrier
>> and you miss them when they're gone, right?
Ron Gabrisko
>> Exactly. I mean, I have some just absolutely great memories building this company, and again, we're just getting started, but the early days to just trying to figure it out were super fun, scaling the company. Literally we've changed, I mean, we've saved people's lives with some of the things we've done in healthcare, but just people in the company.
John Furrier
>> A huge impact.
Ron Gabrisko
>> Yeah, huge impact.
John Furrier
>> Talk about the early days because I find that fascinating. I think you guys not only nailed it, you mentioned the PhDs, Ali and Matei and everyone else. Actually one of the founders was an intern at Cloudera when we started theCUBE.
Ron Gabrisko
>> That's right. That's right.
John Furrier
>> That's how old we're getting. We're 16 years old now with theCUBE.
Ron Gabrisko
>> That's funny.
John Furrier
>> You're seeing we're getting the gray hairs, too. Having an open-source philosophy kind of runs counter to the sales take that hill, hit the quota-
Ron Gabrisko
>> Totally....
John Furrier
>> because you have to rely on pull.
Ron Gabrisko
>> Yep.
John Furrier
>> How did you handle that? How did you guys take that? You got to be aware, but you also have to monetize, which kind of is a subtle art-
Ron Gabrisko
>> Totally....
John Furrier
>> to that piece of the business. It's certainly foundational. What was some of the keys to doing that? Organic, freemium, premium, whatever you want to call it, people are trying to do it. You cracked the code.
Ron Gabrisko
>> Totally. I think we innovated on the business model as much as we did on the technology. Traditional open source was like just self-services and support, and the company's strategy was, "Let's build a managed cloud service." We used to call it open-source core, basically, so build some features that are proprietary that we can monetize. Eventually, though, we continued to innovate in terms of number of features and products. Now, it's not just one. A lot of companies, too, they fail because they build one product and then you can kind of easily replicate that with open source, but we have like now 10 amazing products.
John Furrier
>> You guys became a service provider-
Ron Gabrisko
>> Exactly....
John Furrier
>> to the market that was enabling your success-
Ron Gabrisko
>> Exactly, exactly....
John Furrier
>> and that was the key.
Ron Gabrisko
>> Yeah, and we still embrace open-source community because we're open source. Any of our customers can do whatever they want with their data. We don't own anyone's data, so-
John Furrier
>> Yeah, you-...
Ron Gabrisko
>> if you want to go run it yourself, go run it yourself....
John Furrier
>> by the way, people might not know this, but at Data AI Summit, the keynote is so packed. I'd say maybe half if not two-thirds of the audience are technical developers.
Ron Gabrisko
>> Yeah, they're all developers.
John Furrier
>> They're all developers.
Ron Gabrisko
>> They rush the stage. They knock over the security guards. It's like a rock concert.
John Furrier
>> Yeah, yeah. Watching Ali trying to stay on script is fun to watch.
Ron Gabrisko
>> Yeah. Yeah, he's a character for sure.
John Furrier
>> Well, great to have you on. Again-
Ron Gabrisko
>> Thank you....
John Furrier
>> congratulations. We've been following Databricks, again, from day one, watching you guys innovate. It's been fun to watch and document, and now that you guys are successful, don't forget about us little guys.
Ron Gabrisko
>> Well, thanks for having me. I mean, we're just getting started.
John Furrier
>> You got Agent Bricks, right?
Ron Gabrisko
>> Yeah.
John Furrier
>> Agent Bricks is out.
Ron Gabrisko
>> Agent Bricks is amazing.
John Furrier
>> Agent Bricks.
Ron Gabrisko
>> Lakebase.
John Furrier
>> Do you have Media Bricks yet?
Ron Gabrisko
>> We don't. We need Media Bricks.
John Furrier
>> You need Media Bricks.
Ron Gabrisko
>> We need Media Bricks. I like that. Help us with that. Let's co-develop it.
John Furrier
>> Okay, done.
Ron Gabrisko
>> We can open source it. I love that.
John Furrier
>> Co-design. Let's talk about-
Ron Gabrisko
>> Yeah, very ....
John Furrier
>> co-design. I like this. This is an interesting time because Nvidia talks about this all the time, and you're seeing successful ecosystems develop and the go-to-market is not just sales, it's partner sales-
Ron Gabrisko
>> Massive....
John Furrier
>> ecosystem.
Ron Gabrisko
>> Yep.
John Furrier
>> Talk about how co-design isn't just a technical thing-
Ron Gabrisko
>> Yeah, exactly....
John Furrier
>> because the business model innovation actually is a big story.
Ron Gabrisko
>> If you think about it, the future's going to be all agents. There's not going to be humans creating databases. It's all agentic, coding assistants, all these other applications that are having to create these databases, and so we're co-developing-
John Furrier
>> It's part of your-...
Ron Gabrisko
>> ....
John Furrier
>> go-to-market, right?
Ron Gabrisko
>> Entirely. Exactly.
John Furrier
>> I was talking with Ali, my good friend Pete, and co-founder Andy started Loud Ventures. They did this new incubator research thing. That is huge. Talk about how that's impacting the go-to-market because the role of research isn't like I'm a researcher at Cal or wherever. It's almost applied research. It's almost like go-to-market effect.
Ron Gabrisko
>> Yeah, and we runs tons of startup programs, both with our VCs as well as with... I mean, we have 650 university programs now that run Databricks as part... I mean, being a data scientist and an AI engineer is literally the highest paying job you can get out of college nowadays. We run all those programs to try to just like a VC model. We don't know who's going to be the next Databricks or OpenAI or Anthropic, so we're helping all of them innovate, right?
John Furrier
>> Ron, great to have you on theCUBE.
Ron Gabrisko
>> Yeah .
John Furrier
>> Thanks for coming into our studio.
Ron Gabrisko
>> Absolutely.
John Furrier
>> What do you think about the NYSE-
Ron Gabrisko
>> Oh, man....
John Furrier
>> new studio?
Ron Gabrisko
>> Incredible. Very cool. Very cool.
John Furrier
>> It's quiet now.
Ron Gabrisko
>> Yeah, very cool. I love this.
John Furrier
>> What's that scene from Trading Places? Get those traders back in here. Turn those machines back on."
Ron Gabrisko
>> I love the guy running back and forth yelling at, "Get that trade done. Let's go. That's money."
John Furrier
>> As a CRO, you love the sales culture.
Ron Gabrisko
>> That's right, dude.
John Furrier
>> "Let's get that sale."
Ron Gabrisko
>> He was hustling. I'll hire that guy. I like that.
John Furrier
>> Ron, thanks for coming in.
Ron Gabrisko
>> Yeah, absolutely.
John Furrier
>> CRO of Databricks, breaking down, again, the innovations on the business model, the go-to-market. This is, again, a big part of the value of AI productivity. Agent technology can really solve a lot of those mundane toil problems, but also get down to the precision, and this is where AI certainly will create a lot of value and, again, extract value as well. This is theCUBE doing our part to bring you that value here. Thanks for watching.
>> Welcome back around to theCUBE here at the theCUBE's NYSE East Coast Studios and access point, part of our NYSE Wired communities and open access network, bringing leaders together, so a mixture of experts. We talk about the leaders, where the experts where all the reasoning happens here on theCUBE. We have the CRO from Databricks here. Ron, great to see you. Thanks for coming in.
Ron Gabrisko
>> Thanks for having me. Excited to be here.
John Furrier
>> Chief Revenue Officer of Databricks. Well, first of all, your valuation's awesome. Congratulations on the-
Ron Gabrisko
>> Thank you....
John Furrier
>> monster valuation and the continued growth. We've been following Databricks from day one, going back to the old Hadoop didn't work, Spark comes, data lakes come in, lakehouse, and then just the adoption of having your data act together really kind of sets the table for now what is the dream scenario for that, which is generative AI and-
Ron Gabrisko
>> Really....
John Furrier
>> and all the software and open-source developers leveraging this infrastructure. You guys have been really successful, and also still in a great position, bringing in all kinds of new algorithms, extracting away complexities, making it easier. Ali was on yesterday detailing that out. Quite a run.
Ron Gabrisko
>> Yeah. Thank you. Yeah. No, absolutely incredible. I mean, we're just getting started.
John Furrier
>> How's the revenue numbers?
Ron Gabrisko
>> Doing well. We're doing all right.
John Furrier
>> What's the forecast?
Ron Gabrisko
>> Exactly.
John Furrier
>> Are you guys looking good from, as they say, middle of the fairway in golf?
Ron Gabrisko
>> Yep.
John Furrier
>> You guys have been using AI internally. One of those top stories that I wanted to get in with you is how Databricks has been driving innovation on the data side. Obviously, the Cal pedigree. Now, they've got a great computer science bench, a lot of schools coming together, so the tech, the vision, the strategy all working.
Ron Gabrisko
>> Yep.
John Furrier
>> Now, customers are using it, scaling up with the data lakes, doing a lot more. What are the top things are you seeing from your customers right now in terms of that kind of next-level value from the data lakes as they start to think through how to have a generational platform for generative AI?
Ron Gabrisko
>> I mean, if you think about it, every single one of these companies will become a data and AI company. How they'll compete, win, lose in the market is how they apply AI to their proprietary data, and so it's in every single industry. Like healthcare, we've helped companies discover new cancer drugs, all the cancer treatment stuff. Agents read all your medical records to try to discover drugs for clinical trials, financial services for fraud, I mean, it's every single industry, but a big part of it is how do you apply AI to proprietary data to have a competitive advantage?
John Furrier
>> We're seeing the on-prem adoption with AI factories and other large-scale systems because there's a fear of putting those crown jewels into the public models. The emergence of, and you guys talked about this last year at Data and AI Summit, which is there's a power law of smaller models. They work together and the need for customers to have their own so they can actually apply that to agents.
Ron Gabrisko
>> Yeah, yeah, so I mean, we're entirely in the cloud, so most of the modern data stacks we'll move to the cloud, but the biggest part is we're not doing general intelligence. A lot of the frontier models, if you want to know how did World War II play out, they've been trained on all the internet data. The proprietary data that's inside of companies, applying AI to that to make more strategic or better decisions, or even automate processes, that's how AI gets applied to data. We have partnerships with all the major frontier models, OpenAI, Anthropic, Gemini, Lama, et cetera, and how you can kind of do governance, make sure that your data's secure, that it's not using your data, that's really important for these companies.
John Furrier
>> When they look at those models, they're thinking as a developer perspective, they're trying to build solutions.
Ron Gabrisko
>> Yeah, totally.
John Furrier
>> What's the biggest use case that you guys see in the enterprise right now that's got the most traction, momentum?
Ron Gabrisko
>> I mean, it's all across the board. Like I said, there's massive, and it kind of depends on the industry. Lots of people are trying to automate call centers. I mean, that's kind of bread and butter. Lots of agents doing that. I saw some really cool developments in retail. so they were measuring shrinkage on food shrinkage and spoilage and things of that nature. They had agents to do repricing, agents to do promotions. Just really cool in retail. Lots of sports stuff. The new Fox Sports app, Cleatus, I don't know if you're a sports fan, but that's all AI-driven by Databricks, so .
John Furrier
>> Yeah, people are using the AI agents to make their picks on their fantasy-
Ron Gabrisko
>> Exactly....
John Furrier
>> you know?
Ron Gabrisko
>> Exactly. Mine's not doing too good, but-
John Furrier
>> I'm not going to lie. I definitely when I'm getting my picks in, I didn't put time to prep. I definitely I have gone to the-
Ron Gabrisko
>> Exactly....
John Furrier
>> cheat sheet.
Ron Gabrisko
>> .
John Furrier
>> It's right there. ESPN, they're all publishing their content. I Mean, why not grab it?
Ron Gabrisko
>> Yeah, exactly.
John Furrier
>> All right, as CRO, I want to ask you kind of the revenue question because this comes up a lot on all of our AI series, whether it's AI Leaders, Robotics, Factory, Mixture of Experts, the conversation has shifted over the past year from cost savings. Well, it's always been kind of like, "Oh, you get some cost savings and revenue bump," but no one could really articulate that. Now, it's kind of shifted towards revenue.
Ron Gabrisko
>> Yeah, totally.
John Furrier
>> Knowing Databricks' pedigree technical company, I'm sure you're under pressure to get the AI going for you.
Ron Gabrisko
>> Yeah, for sure.
John Furrier
>> What are you guys doing on the revenue side of CRO? Can you share some of your thoughts around how you're using agents or AI for your team?
Ron Gabrisko
>> Yeah, absolutely. I mean, first of all, as an AI company, we've adopted AI machine learning from the beginning. I would say we were doing AI before AI was cool, and our entire business is built on Databricks. We call it Databricks on Databricks. We have our own lakehouse, we have all our data in there. I can predict our revenue within kind of 1 to 3% down to each customer. I know which customers are going to churn. We have next best action on which solutions we should be selling customers. We automate a lot of the account plans. We're automating some of the account followup like lead followup, things of that nature, so we apply it literally across the business.
John Furrier
>> You use it for qualifying, too, as well?
Ron Gabrisko
>> Yeah, totally, like all in our marketing. Which campaigns should we run? How should we articulate specific email campaigns? Or-
John Furrier
>> All right, what's the-...
Ron Gabrisko
>> you know....
John Furrier
>> coolest thing that's popped out of this that you could share? A story or some bluebird deal came in or why we saved the company from going-
Ron Gabrisko
>> Oh....
John Furrier
>> somewhere else? There's got to be some stories-
Ron Gabrisko
>> I mean-...
John Furrier
>> you know?...
Ron Gabrisko
>> literally, if you look at how we can predict our revenue, like holidays, all that kind of stuff, it follows the predictive line really, really close. If it bumps off of it, we're like, "Why did it?" They're like, "Oh, they had some random holiday in this country that we didn't. It was on a Saturday last year and this year it fell on a Friday." Literally it's that kind of precision. It's pretty cool.
John Furrier
>> Precision helps you guys do what? Adjust the sales tactics, your Biz Dev components?
Ron Gabrisko
>> Again, you're trying to grow the revenue as fast as possible, so knowing what's making that happen. Is it certain AI trends? A lot of the things we're selling into agents, we just crossed a billion dollars in AI revenue. Or is it some of our core data warehousing technology? We'll kind of see all those trends of different products with different customers. We'll know like, "Oh, this customer looks like they're having some trouble. Let's lean in more there with some of our executives or some of our technical folks." So-
John Furrier
>> I was kind of hinting with this yesterday with Ali Ghodsi, who came in yesterday. You guys pretty much nailed the technical buyer over the early years.
Ron Gabrisko
>> Yeah.
John Furrier
>> Data lake, people loved it, saved them money. Knocked down their cloud bill, make it more efficient. You guys went serverless. Okay, that changed the game there, so a lot of technical customers love Databricks.
Ron Gabrisko
>> Yeah, totally.
John Furrier
>> Okay, so now bridge that with the business outcome focus because what we're hearing now from Ali and the team is look at there's real work to be done. Let's just get that done and get the proof points out there. That's a business outcome-
Ron Gabrisko
>> Totally...
John Furrier
>> thinking. Take me through the mindset of how your emotions have changed or your customer behavior. Now you're crossing over into the business realm of-
Ron Gabrisko
>> Totally....
John Furrier
>> what's the value? Can I quantify it?
Ron Gabrisko
>> Yep. Yeah, so I mean, you think about like now AI is a CEO-level discussion,. It's not like a chief data officer. Certainly it's part of the chief data officer and CIO, but it's a CEO. It's like, "How are we leveraging Ai to transform our business so that we don't get disrupted? How do we provide better customer service?" All those things, so it's not about like, "Hey, let's just take out some legacy costs." It's literally like, "How do we transform and offer new services to customers? How do we provide better service to customers? How do we launch new products? How do we open up new regions?" All of that's like more strategic of, "How do I grow my business?" As a strategic advisor to a lot of those customers, we need to know. We need to know more about their business and so how it's going to impact their business and help them with that.
John Furrier
>> You know, last year I noticed Databricks had a big presence at NRF-
Ron Gabrisko
>> Yep....
John Furrier
>> and as did Salesforce and others. I'm like, well, we're going to cover it again this year here out of our studio, but clearly that's an Ai show. MWC, we knew that was an AI show-
Ron Gabrisko
>> Totally....
John Furrier
>> years ago.
Ron Gabrisko
>> Totally.
John Furrier
>> Supercomputing, that was HPC, High-Performance Computing Show now like four years ago, converted to full AI. That's a semiconductor kind of level. Let's take retail for instance. AI can change the go-to-market for any company. That's what you do. You're handling the go-to-market for Databricks.
Ron Gabrisko
>> Yep.
John Furrier
>> What lessons have you guys learned for that practitioner-
Ron Gabrisko
>> Totally....
John Furrier
>> that's saying, "Hey, look, I'm going to get the data set up, my tech team's on it, we're using Databricks?" What's the next chain? Hat's the impact to the executive who's bleeding the go-to-market?
Ron Gabrisko
>> I mean, it's real-time applications for how they run their business, and it goes all the way down to like the distributor or sales rep. If I'm running kind of sales for, say, a soft drink or Pepsi or some of the beer distributors, they're covering these stores, it'll literally tell them like, "Hey, you need to sell more of this kind of coffee," or, "You should run this promotion," or, "You should be doing this." Take a picture display and it'll actually tell you, recommend, "No, put this on the top shelf." Those kind of things, it's pretty amazing. Even down at that level, it's like a cockpit for the distributor or salesperson. Then, if you look at it as an executive, we literally created an application. Like I said, it was the intelligent store and it'll show like, "Okay, this particular store is doing really well. This store is not doing so well. What are the differences? Is it demographics? Are they running different promotions? Do they have a different product mix?" It's actually making real-time recommendations to help you improve your business.
John Furrier
>> A lot of predictive?
Ron Gabrisko
>> A lot of predictions. Exactly.
John Furrier
>> What on the generative AI side, on the customer? Are they having any changes on how-
Ron Gabrisko
>> Totally....
John Furrier
>> their relationship with the customer changes?
Ron Gabrisko
>> I mean, think about it. Now, you're able to talk to your data, so in terms of customer service on agents, any business, you have an issue, you're trying to get service on your vehicle or yo have a return with a retailer, all of that is being automated with agents. It's going to pull your records, your customer service. It's all going to try to automate that. It's going to improve the human service. In some cases it may replace the human service, but in most cases it's like gather all the information and still keep the human element of how you do customer service, so...
John Furrier
>> What's it like being the CRO of Databricks the past decade? I mean, I think you guys are on the Series K. I mean, we might run out of-
Ron Gabrisko
>> We're running out of letters....
John Furrier
>> we might run out of an alphabet. Might go to like hexadecimal or some sort of numeric financing system.
Ron Gabrisko
>> Yeah, exactly.
John Furrier
>> I mean, quite a rocket ship.
Ron Gabrisko
>> It's so fun.
John Furrier
>> What's been the biggest learnings for you at CRO? I mean, you've navigated massive growth while technology change has been happening.
Ron Gabrisko
>> Well, I mean, first of all, we have seven... Should I just keep going?
John Furrier
>> Yeah, it's still going. Yeah-
Ron Gabrisko
>> Yeah, okay....
John Furrier
>> it's an option bell.
Ron Gabrisko
>> All right, no worries.
John Furrier
>> Option market's-
Ron Gabrisko
>> You know-...
John Furrier
>> now closed....
Ron Gabrisko
>> we have seven PhD founders that created one of the greatest pieces of software in the world and just wanted to change the world. They literally gave it away for free, and how we built the business, and we built it together, was we focused a lot on the customer. How do we provide value to the customer? At each phase of the company, you have to kind of change, so as a leader in how I've built the go-to-market trade, I've also had to change. Kind of the zero to 20 or 50 million, it's product-market fit. Hundred million's like how you scale, build a playbook. A billion dollars, much larger scale where you're having to replicate things and grow internationally and grow with partners. Now, we're on hyperscale multiple billions, and so each phase is a little bit different, and so-
John Furrier
>> Which one's your favorite?
Ron Gabrisko
>> Oh, they're all different and they've all been-
John Furrier
>> It's like kids. They're great when they're in elementary school. They get just as hard when they go to the next level-
Ron Gabrisko
>> Yeah, exactly....
John Furrier
>> and you miss them when they're gone, right?
Ron Gabrisko
>> Exactly. I mean, I have some just absolutely great memories building this company, and again, we're just getting started, but the early days to just trying to figure it out were super fun, scaling the company. Literally we've changed, I mean, we've saved people's lives with some of the things we've done in healthcare, but just people in the company.
John Furrier
>> A huge impact.
Ron Gabrisko
>> Yeah, huge impact.
John Furrier
>> Talk about the early days because I find that fascinating. I think you guys not only nailed it, you mentioned the PhDs, Ali and Matei and everyone else. Actually one of the founders was an intern at Cloudera when we started theCUBE.
Ron Gabrisko
>> That's right. That's right.
John Furrier
>> That's how old we're getting. We're 16 years old now with theCUBE.
Ron Gabrisko
>> That's funny.
John Furrier
>> You're seeing we're getting the gray hairs, too. Having an open-source philosophy kind of runs counter to the sales take that hill, hit the quota-
Ron Gabrisko
>> Totally....
John Furrier
>> because you have to rely on pull.
Ron Gabrisko
>> Yep.
John Furrier
>> How did you handle that? How did you guys take that? You got to be aware, but you also have to monetize, which kind of is a subtle art-
Ron Gabrisko
>> Totally....
John Furrier
>> to that piece of the business. It's certainly foundational. What was some of the keys to doing that? Organic, freemium, premium, whatever you want to call it, people are trying to do it. You cracked the code.
Ron Gabrisko
>> Totally. I think we innovated on the business model as much as we did on the technology. Traditional open source was like just self-services and support, and the company's strategy was, "Let's build a managed cloud service." We used to call it open-source core, basically, so build some features that are proprietary that we can monetize. Eventually, though, we continued to innovate in terms of number of features and products. Now, it's not just one. A lot of companies, too, they fail because they build one product and then you can kind of easily replicate that with open source, but we have like now 10 amazing products.
John Furrier
>> You guys became a service provider-
Ron Gabrisko
>> Exactly....
John Furrier
>> to the market that was enabling your success-
Ron Gabrisko
>> Exactly, exactly....
John Furrier
>> and that was the key.
Ron Gabrisko
>> Yeah, and we still embrace open-source community because we're open source. Any of our customers can do whatever they want with their data. We don't own anyone's data, so-
John Furrier
>> Yeah, you-...
Ron Gabrisko
>> if you want to go run it yourself, go run it yourself....
John Furrier
>> by the way, people might not know this, but at Data AI Summit, the keynote is so packed. I'd say maybe half if not two-thirds of the audience are technical developers.
Ron Gabrisko
>> Yeah, they're all developers.
John Furrier
>> They're all developers.
Ron Gabrisko
>> They rush the stage. They knock over the security guards. It's like a rock concert.
John Furrier
>> Yeah, yeah. Watching Ali trying to stay on script is fun to watch.
Ron Gabrisko
>> Yeah. Yeah, he's a character for sure.
John Furrier
>> Well, great to have you on. Again-
Ron Gabrisko
>> Thank you....
John Furrier
>> congratulations. We've been following Databricks, again, from day one, watching you guys innovate. It's been fun to watch and document, and now that you guys are successful, don't forget about us little guys.
Ron Gabrisko
>> Well, thanks for having me. I mean, we're just getting started.
John Furrier
>> You got Agent Bricks, right?
Ron Gabrisko
>> Yeah.
John Furrier
>> Agent Bricks is out.
Ron Gabrisko
>> Agent Bricks is amazing.
John Furrier
>> Agent Bricks.
Ron Gabrisko
>> Lakebase.
John Furrier
>> Do you have Media Bricks yet?
Ron Gabrisko
>> We don't. We need Media Bricks.
John Furrier
>> You need Media Bricks.
Ron Gabrisko
>> We need Media Bricks. I like that. Help us with that. Let's co-develop it.
John Furrier
>> Okay, done.
Ron Gabrisko
>> We can open source it. I love that.
John Furrier
>> Co-design. Let's talk about-
Ron Gabrisko
>> Yeah, very ....
John Furrier
>> co-design. I like this. This is an interesting time because Nvidia talks about this all the time, and you're seeing successful ecosystems develop and the go-to-market is not just sales, it's partner sales-
Ron Gabrisko
>> Massive....
John Furrier
>> ecosystem.
Ron Gabrisko
>> Yep.
John Furrier
>> Talk about how co-design isn't just a technical thing-
Ron Gabrisko
>> Yeah, exactly....
John Furrier
>> because the business model innovation actually is a big story.
Ron Gabrisko
>> If you think about it, the future's going to be all agents. There's not going to be humans creating databases. It's all agentic, coding assistants, all these other applications that are having to create these databases, and so we're co-developing-
John Furrier
>> It's part of your-...
Ron Gabrisko
>> ....
John Furrier
>> go-to-market, right?
Ron Gabrisko
>> Entirely. Exactly.
John Furrier
>> I was talking with Ali, my good friend Pete, and co-founder Andy started Loud Ventures. They did this new incubator research thing. That is huge. Talk about how that's impacting the go-to-market because the role of research isn't like I'm a researcher at Cal or wherever. It's almost applied research. It's almost like go-to-market effect.
Ron Gabrisko
>> Yeah, and we runs tons of startup programs, both with our VCs as well as with... I mean, we have 650 university programs now that run Databricks as part... I mean, being a data scientist and an AI engineer is literally the highest paying job you can get out of college nowadays. We run all those programs to try to just like a VC model. We don't know who's going to be the next Databricks or OpenAI or Anthropic, so we're helping all of them innovate, right?
John Furrier
>> Ron, great to have you on theCUBE.
Ron Gabrisko
>> Yeah .
John Furrier
>> Thanks for coming into our studio.
Ron Gabrisko
>> Absolutely.
John Furrier
>> What do you think about the NYSE-
Ron Gabrisko
>> Oh, man....
John Furrier
>> new studio?
Ron Gabrisko
>> Incredible. Very cool. Very cool.
John Furrier
>> It's quiet now.
Ron Gabrisko
>> Yeah, very cool. I love this.
John Furrier
>> What's that scene from Trading Places? Get those traders back in here. Turn those machines back on."
Ron Gabrisko
>> I love the guy running back and forth yelling at, "Get that trade done. Let's go. That's money."
John Furrier
>> As a CRO, you love the sales culture.
Ron Gabrisko
>> That's right, dude.
John Furrier
>> "Let's get that sale."
Ron Gabrisko
>> He was hustling. I'll hire that guy. I like that.
John Furrier
>> Ron, thanks for coming in.
Ron Gabrisko
>> Yeah, absolutely.
John Furrier
>> CRO of Databricks, breaking down, again, the innovations on the business model, the go-to-market. This is, again, a big part of the value of AI productivity. Agent technology can really solve a lot of those mundane toil problems, but also get down to the precision, and this is where AI certainly will create a lot of value and, again, extract value as well. This is theCUBE doing our part to bring you that value here. Thanks for watching.