Alteryx Inspire 2024 | Suresh Vittal | Alteryx

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Suresh Vittal

Chief Product Officer

Alteryx

How Alteryx AiDIN Copilot transforms data analytics with cutting-edge AI workflow efficiency

Since the modern enterprise world is requiring a nexus of data and artificial intelligence, streamlining analytical workflows is vital, and this is why AiDIN Copilot comes in handy for enhanced business efficiency. AiDIN Copilot is proving to be a game-changer since its an AI-powered analytics companion that accelerates workflow creation and provides instant answers and recommendations, according to Suresh Vittal (pictured), chief product officer of Alteryx Inc.Alteryx’s Suresh Vittal talks to theCUBE about the importance of AiDIN Copilot and Auto Insights.“In the AI category, we announced AiDIN Copilot,” Vittal stated

play_circle_outline Revolutionizing Product Innovation: Unveiling the Cutting-Edge AI and Cloud Enhancements like Aiden Copilot and Auto Insights

play_circle_outline Transforming Data Integration: Revolutionizing AI with Seamless Database Integration

play_circle_outline The Significance of Collaboration: Leveraging Partnerships with GSIs, Bars, and Emerging Players for Cloud and On-Prem Flexibility

play_circle_outline Maximizing Investment for Designer and Server Capabilities: Delivering Easy-to-Use, Innovative Applications with Generative AI

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Suresh Vittal | Alteryx

Suresh Vittal

Chief Product Officer Alteryx

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Rebecca Knight

>> Hello, everyone. And welcome back to The Cube's Live coverage of Alteryx Inspire here at the Venetian in Las Vegas. I'm your host, Rebecca Knight. Sitting alongside my co-host and analyst, Rob Streche. We're just fresh from lunch where we had so many great conversations with many of the attendees here and it's really coming through what a community this is of innovators.

>> What I loved is some people sitting together, sharing ideas on workflows-

Rebecca Knight

>> Helping each other out.

>> Again, I just love that when you come to an event, and I think that really carried over from the keynote this morning because the energy and just the customer use cases and the discussions were killer. And the demos were, I thought, the weaving DoorDash throughout was fantastic.

Rebecca Knight

>> A good thread. A good thread indeed. Well, speaking of all of that, who better to talk about the product innovation that's taking place at Alteryx than Suresh Patel? He is the chief product officer here at Alteryx. Thank you so much for coming on The Cube.

>> Thanks for having me.

Rebecca Knight

>> Another Bostonian. So here we can talk about Boston sports or we can talk about products.

>> And Cube alumni.

Rebecca Knight

>> Exactly. I should say that. Exactly. As Rob was saying, we saw a lot of exciting new product innovations and enhancements in the keynotes today. Why don't you just walk us through them a little bit and tell our viewers a little bit more what happened?

>> Thank you for being here, firstly. We've got 3,500 of our customers with us today and tomorrow going to certifications, training, and knowledge sharing. I think we announced a lot of exciting stuff here at Inspire. I'll break the announcements down in two big categories. Certainly, AI is a very resonant theme with our customers and certainly was a resonant with our product strategy as well. And so we talked a lot about how we are using AI to make the lives of our users much simpler, allowing them to do analytics better and faster and create more insights, frankly, across the business. So in the AI category, we announced Aiden Copilot, which I'm super excited about. You all saw a demo.

Rebecca Knight

>> Oh, the demo was really great, right? I was excited after seeing the demo

>> Right. And DoorDash was literally going to... He was writing his prompt in of what he wanted to do, and that's the power of Aiden Copilot. It is your personal assistant to help you build workflows faster and do better analytics, and we think that's going to be a game changer because it's going to lower the barriers to entry in the user and getting value out of our products. We also announced in Auto Insights a series of AI capabilities, one called Playbooks, which kind of speedens up the ideation process and allows you to think about the use cases and bring products to life quickly and bring ideas to life quickly, all the way to the process of building the workflow. It recommends to you what use cases you'd be focused on. And then of course, we talked about in Auto Insights, we talk about Magic pages and Magic documents, which accelerates the analytics process. So lots of announcements on AI side and then cloud announcements as well. We made a series of cloud announcements, availability of design, a cloud and auto insights and location intelligence across all platforms, GCP, AWS, and Azure. We talked about all the use cases that they could do on the desktop and they can now do it in the cloud with for prep, blend, and transform with Design a Cloud. So we announced all of those new capabilities as well. I'm super excited, as you can hear, lots of AI announcements and a lot of cloud announcements.

>> Yeah, I think again, it was such a good announcement and I think what has been that other theme has been going through has been partnership and things, you had Databricks up there and which again, it's really that nexus between cloud and data and AI. And I think to your point, AI and Aiden, which you announced last year, but really brought to life this year, what are some of the use cases you see that people are going to really lean in on and use that? Because I think that to me is what makes it real to people as well.

>> Yeah, so I think that's great how you phrased it, nexus of AI, cloud, and analytics, and that's really important for us. We want customers to be using these products to solve real-world use cases. I see them using Aiden, for example, for our co-pilot capabilities to really accelerate the process of learning more around the product. It's not just about doing the workflow, but it's about bringing transparency to what they build and what the systems build. We've all heard about cases where the AI is hallucinating or it's providing misinformation or it's biased in some shape or form. We've built it in a way where it's completely transparent, and so we want them to learn more about the workflow that they're building and what better way to do it than have the system coach you on what you should be doing. So I think that contextual help and the transparencies, the use case that people are going to really grab onto and use it to bring new users into the family faster, we think a lot of what I would think of as core activities that you have to do, I think those are going to become faster. So you saw us talk about Magic Pages and Magic Documents. I can see a whole host of users using it to create personalized reporting aimed at specific individuals inside the company. I think that's a use case that's going to take off golf.

>> Yeah, I think so. And I think to your point, I think what was really interesting is it's not AI for AI's sake. And like you said, and I love the fact that you're putting guardrails there, and I think you talked to that and I loved the little map and all of that and the rerouting, because I swear Waze takes me the wrong way, just save me one minute and I'm like, "I got to get off and get back on."

Rebecca Knight

>> I don't mind that. I actually, I like it.

>> But I think to your point, it's like you want to trust it, right? That's cool.

Rebecca Knight

>> That was one of our... So we are really thinking hard about how do you allow for responsible AI inside the business. So we want our users to be able to benefit from AI, but we want to put the guardrails in place as well. So they get the right governance, they get the right protection, they're able to open that black box and look inside and understand what the model's proposing and if that's the right answer or not. And so we are trying to draw this balance between usability because that's what we're known for, right? Alteryx products are amazing to use, easy to use, lower the barriers to entry. So we want a balance between usability, access to AI. You don't need to be a data scientist to use our products, and we want you to be able to build models and be able to use all of these capabilities. And third, we want you to be responsible and transparent.

Rebecca Knight

>> I love that you don't have to be a data science to use it. I mean, that was really stressed today during the keynote that this is use plain English, we can get you, but we got you, got your back. In terms of your overall approach, I mean, you are the head of product and you are supposed to be thinking innovative thoughts. That's what you get paid for. But how do you think about AI in terms of what you were just saying is that AI makes mistakes. It hallucinates. You can't always trust it. It's not always ethical, it's biased. How do you think about these things, approach these things and then lead a team to also have that perhaps right amount of skepticism they're when they're creating new products?

>> Yeah, we are deeply thoughtful about how we want to approach AI. We don't want to make this... We don't want to move too far away from our core ethos, which is about putting analytics in the hands of the business users who understand the business problems, who are starting getting a better understanding of the data, but don't have all the tools that they need to be able to deliver insights to their business. So when we think about our problem statement, we always keep the citizen data scientists or the business analysts front and center and think about what are the problems these people are trying to solve. They're trying to do analytics faster. They're trying to solve for the data processing challenges and they're trying to clean up a lot of these old processes that were put in place from 20 years ago. AI can be helpful in each one of these areas. And so we do a lot of user studies. We run a design partner program. We've got about 50 customers at any given time providing feedback to all our early stage products, and they're providing brutally honest feedback to us and sharing where they think our proposals will work and equally where they won't work and what we can do differently. So we run this through a process because this entire paradigm of AI infused applications is new, and so we need to figure out how to bring workflows, the user experience, and AI together into one blended experience for those users. So we use the design partner program and now we have them in private preview for a period of time where we get even more feedback and we get even wider adoption. And eventually we kind of put it in general availability. So we are constantly thinking about how does this impact the life of the user and how does it allow them to do analytics better, faster, cheaper?

Rebecca Knight

>> Yeah. I think also I think, again, you guys started out on-prem, now you're moving to cloud, you're making connections between the two, why do the right work in the right place? And you're bringing certain features that take advantage of the scale of cloud as well. It would seem that, I mean, again, some of the other announcements besides Aiden that you went into, one that stood out to me and just because I'm a nerd in this stuff is that the metadata not only having to be in Mongo, but now you can be put it in SQL Server for server, Alteryx Server, and so things like that. What other things should organizations be aware of beyond the GenAI stuff that you were announcing today?

>> I mean, you brought a great one up. The availability of it's been a long-standing request for us to make more databases available to play with Alteryx Server. Now we have SQL Server as another place where you can store your Alteryx metadata in. We talked about the cloud availability. You brought that up as well, right? We were available on AWS, we're available on GCP and Azure. I think that's going to unlock a lot of usage for our customers. The third thing we talked about, which may have gone in all the news we announced may have gone, we talked about the security certification, the private data handling. So we think this is a really important capability that customers will need more and more of, which is, I'm going to design in your environment, but I'm going to run in my environment where my data sits and where my data resides. And private data handling gives them exactly that capability. It allows them to run these workflows, these very complex workflows without having to move the data. So in some ways it's bringing the analytics to where the data sits as opposed to taking the data to where the analytics is.

>> Yeah, I think we actually talk about that a lot about bringing AI to the data. And I think, again, when you start to look at where the data is, I mean there's a reason that Databricks has $2 billion in revenue, I mean, Spark and things of that Mongo and others that are up in cloud. And you had Redshift and a number of other databases there that you're connecting to and working with. And do you see that a big piece of where organizations are really... Because it's bridging that. It's bridging from Excel spreadsheets all the way up to Redshift and Databricks, and the data doesn't just sit in one place as well. And that would mean that to me is where the power of workflows comes in.

>> 100%. And that's what we thought about. We want all tricks to be available wherever you work. You are in Snowflake and there's a lot of customers in Snowflake. We want you to be able to run this workflow in Snowflake and push down into Snowflake. You saw Adam Conway on stage there, the SVP of product for Databricks, and he talked about the partnership they have with us, right? 600 plus customers, hundreds of thousands of workflows running in Databricks. Why? Because we are deeply integrated Databricks and we push right down into Databricks, similarly, GCP and the BigQuery customers, Redshift customers, this ability to take these really complex, really articulate, sophisticated workflows down to where the data resides. I think that's a superpower that Alteryx gives our users that's hot to replicate.

Rebecca Knight

>> Suresh, what are you hearing here at Inspire? There's so many great conversations that are taking place in the hallway as well as also in sessions. What are some of the conversations that you're having with customers or partners that you're excited to go back to work on Monday and get started?

>> So that's a great question. Responsible AI is a topic that keeps coming up over and over again. Customers want to be able to do AI but want to do it in a responsible, transparent way, and they want to understand what the playbook is. And we know that's changing quickly with all the announcements that are coming out of the foundation, large language models, the hyperscalers and the cloud warehouse vendors, and Alteryx is a key player in that ecosystem. So responsible AI is a topic that comes up over and over again, the ability to innovate quickly. Our customers are looking to innovate fast, create analytical applications fast, deploy them to their end users quickly. That's a theme that keeps coming back up over and over again. So that's a topic that we talk about. This being able to run on desktop in cloud and in a hybrid requires, our customers to think differently about their architecture. One customer said a really interesting thing to me, financial services customer said, "Hey, you know what? Alteryx is kind of the platform we can bet on that makes it easier for us to change our decisions on everything else." So today, we may be on Google. Tomorrow, we may be on AWS. Alteryx still works. It gives you that flexibility, right? That's a topic that keeps coming up over and over again as well.

Rebecca Knight

>> And I think that to us, we have a partnership with a company called ETR, and we look at the data about where people have been building their next-gen apps, their cloud-native apps, and it really has actually gotten into balance about fifty-fifty between on-prem and in the cloud and on-prem can mean COLO and other things. And I know you work with MSPs and others as well. I think the partnerships, to me, that's been a strength and we had Infosys on earlier and they had won last year, and I think when you start to look at this, do you see the GSIs, the bars and partners, they have to be an integral part of not only getting new customers, but bringing feedback into your organization?

>> 100%. I mean, you saw Databricks on stage, Databricks, Snowflake, the hyperscalers, all really important partners for us. But then the Accenture's, the PWCs, the Deloitte's also important partners for us, but we also have a whole host of emerging players who partner with us, like Fiddler and so on, who are building innovations on top of the Alteryx platform. One data point. We launched the Alteryx marketplace about six months ago to give our partners the ability to build and deliver innovation on top of the platform. Most-adopted capability we've delivered in our history. So again, it shows you the energy the ecosystem has on wanting to build innovation on top of the Alteryx platform.

>> Yeah, no, I think that to me is one of the killer pieces of it, is that it is about innovation and where it makes sense. So what's next? Last word, what's next for Alteryx and where to go?

>> I think we'll continue to make our products easy to use, right? That's the core philosophy. It's kind of the ethos this company's built on. We really want our end users to be successful with the product. We'll continue to do that. You continue to see our innovation in cloud scale, but along that, we know it's just a form factor thing. Designer and server continue to be big investment areas for us, and we'll continue to deliver those capabilities. We've got a few things on generative AI that I can't talk about right now that are coming that I'll give a clue. It'll make it really easy for our users to build analytical applications.

>> Excellent.

Rebecca Knight

>> Suresh, we are on tender hooks, so we'll have to save it for next time. Suresh, always a pleasure. Thank you so much for coming on.

>> It was great to spend time with both of you. Thank you.

Rebecca Knight

>> Stay tuned for more of The Cube's live coverage of Alteryx Inspire. I'm your host Rebecca Knight for Rob Streche. You're watching The Cube, the leader in technology news, coverage, and analysis.

Suresh Vittal | Alteryx

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Rebecca Knight

>> Hello, everyone. And welcome back to The Cube's Live coverage of Alteryx Inspire here at the Venetian in Las Vegas. I'm your host, Rebecca Knight. Sitting alongside my co-host and analyst, Rob Streche. We're just fresh from lunch where we had so many great conversations with many of the attendees here and it's really coming through what a community this is of innovators.

>> What I loved is some people sitting together, sharing ideas on workflows-

Rebecca Knight

>> Helping each other out.

>> Again, I just love that when you come to an event, and I think that really carried over from the keynote this morning because the energy and just the customer use cases and the discussions were killer. And the demos were, I thought, the weaving DoorDash throughout was fantastic.

Rebecca Knight

>> A good thread. A good thread indeed. Well, speaking of all of that, who better to talk about the product innovation that's taking place at Alteryx than Suresh Patel? He is the chief product officer here at Alteryx. Thank you so much for coming on The Cube.

>> Thanks for having me.

Rebecca Knight

>> Another Bostonian. So here we can talk about Boston sports or we can talk about products.

>> And Cube alumni.

Rebecca Knight

>> Exactly. I should say that. Exactly. As Rob was saying, we saw a lot of exciting new product innovations and enhancements in the keynotes today. Why don't you just walk us through them a little bit and tell our viewers a little bit more what happened?

>> Thank you for being here, firstly. We've got 3,500 of our customers with us today and tomorrow going to certifications, training, and knowledge sharing. I think we announced a lot of exciting stuff here at Inspire. I'll break the announcements down in two big categories. Certainly, AI is a very resonant theme with our customers and certainly was a resonant with our product strategy as well. And so we talked a lot about how we are using AI to make the lives of our users much simpler, allowing them to do analytics better and faster and create more insights, frankly, across the business. So in the AI category, we announced Aiden Copilot, which I'm super excited about. You all saw a demo.

Rebecca Knight

>> Oh, the demo was really great, right? I was excited after seeing the demo

>> Right. And DoorDash was literally going to... He was writing his prompt in of what he wanted to do, and that's the power of Aiden Copilot. It is your personal assistant to help you build workflows faster and do better analytics, and we think that's going to be a game changer because it's going to lower the barriers to entry in the user and getting value out of our products. We also announced in Auto Insights a series of AI capabilities, one called Playbooks, which kind of speedens up the ideation process and allows you to think about the use cases and bring products to life quickly and bring ideas to life quickly, all the way to the process of building the workflow. It recommends to you what use cases you'd be focused on. And then of course, we talked about in Auto Insights, we talk about Magic pages and Magic documents, which accelerates the analytics process. So lots of announcements on AI side and then cloud announcements as well. We made a series of cloud announcements, availability of design, a cloud and auto insights and location intelligence across all platforms, GCP, AWS, and Azure. We talked about all the use cases that they could do on the desktop and they can now do it in the cloud with for prep, blend, and transform with Design a Cloud. So we announced all of those new capabilities as well. I'm super excited, as you can hear, lots of AI announcements and a lot of cloud announcements.

>> Yeah, I think again, it was such a good announcement and I think what has been that other theme has been going through has been partnership and things, you had Databricks up there and which again, it's really that nexus between cloud and data and AI. And I think to your point, AI and Aiden, which you announced last year, but really brought to life this year, what are some of the use cases you see that people are going to really lean in on and use that? Because I think that to me is what makes it real to people as well.

>> Yeah, so I think that's great how you phrased it, nexus of AI, cloud, and analytics, and that's really important for us. We want customers to be using these products to solve real-world use cases. I see them using Aiden, for example, for our co-pilot capabilities to really accelerate the process of learning more around the product. It's not just about doing the workflow, but it's about bringing transparency to what they build and what the systems build. We've all heard about cases where the AI is hallucinating or it's providing misinformation or it's biased in some shape or form. We've built it in a way where it's completely transparent, and so we want them to learn more about the workflow that they're building and what better way to do it than have the system coach you on what you should be doing. So I think that contextual help and the transparencies, the use case that people are going to really grab onto and use it to bring new users into the family faster, we think a lot of what I would think of as core activities that you have to do, I think those are going to become faster. So you saw us talk about Magic Pages and Magic Documents. I can see a whole host of users using it to create personalized reporting aimed at specific individuals inside the company. I think that's a use case that's going to take off golf.

>> Yeah, I think so. And I think to your point, I think what was really interesting is it's not AI for AI's sake. And like you said, and I love the fact that you're putting guardrails there, and I think you talked to that and I loved the little map and all of that and the rerouting, because I swear Waze takes me the wrong way, just save me one minute and I'm like, "I got to get off and get back on."

Rebecca Knight

>> I don't mind that. I actually, I like it.

>> But I think to your point, it's like you want to trust it, right? That's cool.

Rebecca Knight

>> That was one of our... So we are really thinking hard about how do you allow for responsible AI inside the business. So we want our users to be able to benefit from AI, but we want to put the guardrails in place as well. So they get the right governance, they get the right protection, they're able to open that black box and look inside and understand what the model's proposing and if that's the right answer or not. And so we are trying to draw this balance between usability because that's what we're known for, right? Alteryx products are amazing to use, easy to use, lower the barriers to entry. So we want a balance between usability, access to AI. You don't need to be a data scientist to use our products, and we want you to be able to build models and be able to use all of these capabilities. And third, we want you to be responsible and transparent.

Rebecca Knight

>> I love that you don't have to be a data science to use it. I mean, that was really stressed today during the keynote that this is use plain English, we can get you, but we got you, got your back. In terms of your overall approach, I mean, you are the head of product and you are supposed to be thinking innovative thoughts. That's what you get paid for. But how do you think about AI in terms of what you were just saying is that AI makes mistakes. It hallucinates. You can't always trust it. It's not always ethical, it's biased. How do you think about these things, approach these things and then lead a team to also have that perhaps right amount of skepticism they're when they're creating new products?

>> Yeah, we are deeply thoughtful about how we want to approach AI. We don't want to make this... We don't want to move too far away from our core ethos, which is about putting analytics in the hands of the business users who understand the business problems, who are starting getting a better understanding of the data, but don't have all the tools that they need to be able to deliver insights to their business. So when we think about our problem statement, we always keep the citizen data scientists or the business analysts front and center and think about what are the problems these people are trying to solve. They're trying to do analytics faster. They're trying to solve for the data processing challenges and they're trying to clean up a lot of these old processes that were put in place from 20 years ago. AI can be helpful in each one of these areas. And so we do a lot of user studies. We run a design partner program. We've got about 50 customers at any given time providing feedback to all our early stage products, and they're providing brutally honest feedback to us and sharing where they think our proposals will work and equally where they won't work and what we can do differently. So we run this through a process because this entire paradigm of AI infused applications is new, and so we need to figure out how to bring workflows, the user experience, and AI together into one blended experience for those users. So we use the design partner program and now we have them in private preview for a period of time where we get even more feedback and we get even wider adoption. And eventually we kind of put it in general availability. So we are constantly thinking about how does this impact the life of the user and how does it allow them to do analytics better, faster, cheaper?

Rebecca Knight

>> Yeah. I think also I think, again, you guys started out on-prem, now you're moving to cloud, you're making connections between the two, why do the right work in the right place? And you're bringing certain features that take advantage of the scale of cloud as well. It would seem that, I mean, again, some of the other announcements besides Aiden that you went into, one that stood out to me and just because I'm a nerd in this stuff is that the metadata not only having to be in Mongo, but now you can be put it in SQL Server for server, Alteryx Server, and so things like that. What other things should organizations be aware of beyond the GenAI stuff that you were announcing today?

>> I mean, you brought a great one up. The availability of it's been a long-standing request for us to make more databases available to play with Alteryx Server. Now we have SQL Server as another place where you can store your Alteryx metadata in. We talked about the cloud availability. You brought that up as well, right? We were available on AWS, we're available on GCP and Azure. I think that's going to unlock a lot of usage for our customers. The third thing we talked about, which may have gone in all the news we announced may have gone, we talked about the security certification, the private data handling. So we think this is a really important capability that customers will need more and more of, which is, I'm going to design in your environment, but I'm going to run in my environment where my data sits and where my data resides. And private data handling gives them exactly that capability. It allows them to run these workflows, these very complex workflows without having to move the data. So in some ways it's bringing the analytics to where the data sits as opposed to taking the data to where the analytics is.

>> Yeah, I think we actually talk about that a lot about bringing AI to the data. And I think, again, when you start to look at where the data is, I mean there's a reason that Databricks has $2 billion in revenue, I mean, Spark and things of that Mongo and others that are up in cloud. And you had Redshift and a number of other databases there that you're connecting to and working with. And do you see that a big piece of where organizations are really... Because it's bridging that. It's bridging from Excel spreadsheets all the way up to Redshift and Databricks, and the data doesn't just sit in one place as well. And that would mean that to me is where the power of workflows comes in.

>> 100%. And that's what we thought about. We want all tricks to be available wherever you work. You are in Snowflake and there's a lot of customers in Snowflake. We want you to be able to run this workflow in Snowflake and push down into Snowflake. You saw Adam Conway on stage there, the SVP of product for Databricks, and he talked about the partnership they have with us, right? 600 plus customers, hundreds of thousands of workflows running in Databricks. Why? Because we are deeply integrated Databricks and we push right down into Databricks, similarly, GCP and the BigQuery customers, Redshift customers, this ability to take these really complex, really articulate, sophisticated workflows down to where the data resides. I think that's a superpower that Alteryx gives our users that's hot to replicate.

Rebecca Knight

>> Suresh, what are you hearing here at Inspire? There's so many great conversations that are taking place in the hallway as well as also in sessions. What are some of the conversations that you're having with customers or partners that you're excited to go back to work on Monday and get started?

>> So that's a great question. Responsible AI is a topic that keeps coming up over and over again. Customers want to be able to do AI but want to do it in a responsible, transparent way, and they want to understand what the playbook is. And we know that's changing quickly with all the announcements that are coming out of the foundation, large language models, the hyperscalers and the cloud warehouse vendors, and Alteryx is a key player in that ecosystem. So responsible AI is a topic that comes up over and over again, the ability to innovate quickly. Our customers are looking to innovate fast, create analytical applications fast, deploy them to their end users quickly. That's a theme that keeps coming back up over and over again. So that's a topic that we talk about. This being able to run on desktop in cloud and in a hybrid requires, our customers to think differently about their architecture. One customer said a really interesting thing to me, financial services customer said, "Hey, you know what? Alteryx is kind of the platform we can bet on that makes it easier for us to change our decisions on everything else." So today, we may be on Google. Tomorrow, we may be on AWS. Alteryx still works. It gives you that flexibility, right? That's a topic that keeps coming up over and over again as well.

Rebecca Knight

>> And I think that to us, we have a partnership with a company called ETR, and we look at the data about where people have been building their next-gen apps, their cloud-native apps, and it really has actually gotten into balance about fifty-fifty between on-prem and in the cloud and on-prem can mean COLO and other things. And I know you work with MSPs and others as well. I think the partnerships, to me, that's been a strength and we had Infosys on earlier and they had won last year, and I think when you start to look at this, do you see the GSIs, the bars and partners, they have to be an integral part of not only getting new customers, but bringing feedback into your organization?

>> 100%. I mean, you saw Databricks on stage, Databricks, Snowflake, the hyperscalers, all really important partners for us. But then the Accenture's, the PWCs, the Deloitte's also important partners for us, but we also have a whole host of emerging players who partner with us, like Fiddler and so on, who are building innovations on top of the Alteryx platform. One data point. We launched the Alteryx marketplace about six months ago to give our partners the ability to build and deliver innovation on top of the platform. Most-adopted capability we've delivered in our history. So again, it shows you the energy the ecosystem has on wanting to build innovation on top of the Alteryx platform.

>> Yeah, no, I think that to me is one of the killer pieces of it, is that it is about innovation and where it makes sense. So what's next? Last word, what's next for Alteryx and where to go?

>> I think we'll continue to make our products easy to use, right? That's the core philosophy. It's kind of the ethos this company's built on. We really want our end users to be successful with the product. We'll continue to do that. You continue to see our innovation in cloud scale, but along that, we know it's just a form factor thing. Designer and server continue to be big investment areas for us, and we'll continue to deliver those capabilities. We've got a few things on generative AI that I can't talk about right now that are coming that I'll give a clue. It'll make it really easy for our users to build analytical applications.

>> Excellent.

Rebecca Knight

>> Suresh, we are on tender hooks, so we'll have to save it for next time. Suresh, always a pleasure. Thank you so much for coming on.

>> It was great to spend time with both of you. Thank you.

Rebecca Knight

>> Stay tuned for more of The Cube's live coverage of Alteryx Inspire. I'm your host Rebecca Knight for Rob Streche. You're watching The Cube, the leader in technology news, coverage, and analysis.