00:14:08 · Neil C. Hughes, Stephen Deasy
[00:14:08] S0: And again, going back to the return on investment, sorry to go back to that. I know it's such a big topic right now. When people are measuring it, I think it's very difficult to know what metrics to measure. So is it faster decision making, lower operating costs, better better customer experience, all of these things or something else? How do you measure that ROI? [00:14:28] S1: I think it's... It is it is all of those things, and it it varies. So what we see with our customers with Streamhouse architectures is operational use cases like observability. We see financial use cases like fraud detection. So another exciting announcement today was the managed model inference. So now on Confluent Cloud, you can connect up to models that we will run for you. We introduced Google and IBM time series for things like anomaly detection. [00:14:59] S0: Yeah. [00:15:00] S1: So whether it's an observability use case or a fraud detection use case, things like that, we're now able to provide the plug ins for those in addition to your own proprietary capabilities within that Streamhouse architecture, that goes back then to unlocking the business value quickly so that you're not spending time standing up and building infrastructure. Instead, you're solving real business problems with the data you have in a secure, governed environment.
00:15:00 · Stephen Deasy, Neil C. Hughes
[00:15:00] S1: So whether it's an observability use case or a fraud detection use case, things like that, we're now able to provide the plug ins for those in addition to your own proprietary capabilities within that Streamhouse architecture, that goes back then to unlocking the business value quickly so that you're not spending time standing up and building infrastructure. Instead, you're solving real business problems with the data you have in a secure, governed environment. [00:15:29] S0: And one of the things I always try and do on this podcast every day is bust a few myths and misconceptions. Now as someone that will spend a lot of time, not only in the technical environment, but also doom scrolling down your phone, you probably see a lot of information on LinkedIn, etc. Are there any misconceptions that enterprises have about what they need to change to make what we're talking about work today? It's a good question. Yeah. Yeah. There can be so many different frustrations, and I just wondered if there are any trends in the kind of questions that people are asking all the kind of things that they have in their head.
00:16:00 · Stephen Deasy
[00:16:00] S1: Well, one... I I think one of the interesting conversations that I'm having at Current today and and and with customers is that... I don't think it's a misconception. I think it's actually what we hear from customers is almost an affirmation that what we're describing in Streamhouse and how it works in the various components actually resonate not because it's new or somehow revolutionary. It's actually putting a name on things that people have already been doing. Streaming the data, governing the data, processing it, and now querying that in real time is something that people have been doing and are feeling even more opportunity or challenge to do because AI is pushing everything so real time that maybe it's that Streamhouse finally gives a name to what people have been feeling and helps then categorize those different pieces that you need. So the nice part about Streamhouse is that this is something we launched as an industry category. This was not a Confluent proprietary. So streamhouse.com is a number of vendors and players in the space that came together and described it, and then we believe we have the best data streaming platform that provides a Streamhouse to you. And so when we talk to customers about that, there's a lot of, oh, that helps me frame a thing I've been seeing and feeling, and now I can use.
00:17:27 · Neil C. Hughes, Stephen Deasy
[00:17:27] S0: Love it. And if I had a virtual crystal ball here I ask you to look into, if we look ahead to the next one, two, three years into the future, how do you see that relationship between AI agents and enterprise data? How do you see that changing or evolving? And what what should business and tech leaders be doing today to prepare for that future in your mind? [00:17:46] S1: Yeah. What what what we see with, you know, we have a data streaming report that we've put out, and there's other data that are out there. And and what we see is a number of of things. Number one, you know, less than a third of customers have brought these agentic work... You know, workflows into production, and nearly two thirds of enterprises report that data is one of the key blockers to bringing those in. And so what I see happening in the next year or two is that as you unlock these use cases and realize the value of the data you already have, you start to crest that wave, if you will. And so I think what we see and what we're hearing again is that this helps unblock those. So my prediction would be that those rates go up significantly in terms of production workloads coming in because we see solutions like the Streamhouse unblocking or or or working against some of the major blockers that we hear from customers that are preventing them getting there.
00:17:46 · Stephen Deasy, Neil C. Hughes
[00:17:46] S1: Yeah. What what what we see with, you know, we have a data streaming report that we've put out, and there's other data that are out there. And and what we see is a number of of things. Number one, you know, less than a third of customers have brought these agentic work... You know, workflows into production, and nearly two thirds of enterprises report that data is one of the key blockers to bringing those in. And so what I see happening in the next year or two is that as you unlock these use cases and realize the value of the data you already have, you start to crest that wave, if you will. And so I think what we see and what we're hearing again is that this helps unblock those. So my prediction would be that those rates go up significantly in terms of production workloads coming in because we see solutions like the Streamhouse unblocking or or or working against some of the major blockers that we hear from customers that are preventing them getting there. [00:18:46] S0: And there are so many people here at the moment. I'm conscious you must have back to back meetings, meetings with customers, meetings with people like me. Not only that, there's a lot of keynotes and conversations on the show floor. If you were to put all those conversations into, I don't know, an LLM, what would you be taking away from the event? What are going be thinking about on that plane ride,
00:18:46 · Neil C. Hughes, Stephen Deasy
[00:18:46] S0: And there are so many people here at the moment. I'm conscious you must have back to back meetings, meetings with customers, meetings with people like me. Not only that, there's a lot of keynotes and conversations on the show floor. If you were to put all those conversations into, I don't know, an LLM, what would you be taking away from the event? What are going be thinking about on that plane ride, [00:19:06] S1: This might this might sound trite, but I I I really do believe that the the energy that we're feeling from people around this Streamhouse capability and, like, explaining how it flows together really has clicked for people. And so whether it's the practitioners in our customers, whether it's the CIOs, whether it's the business side, what we're hearing across the board is, yes, this describes what I'm feeling. Yes, this shows me how I can achieve this. And I'm excited because, again, it's something that I can tap into with what I already have. I'm not starting from scratch. And we're not proposing that you throw out the investments you've made quite the opposite. We're saying they actually allow you to build into what we've got, and now with these additional capabilities, these, you know, these capabilities now unblock workloads for you. So I would say that that's probably the most exciting part when you come to an event like this. You always have some anxiety about will this land? Is it is it what people are are needing and wanting? And I think we've we've seen really positive, you know, excitement about that.