1 00:00:04,720 --> 00:00:11,160 This is identity at the center. Welcome to the Identity at the 2 00:00:11,160 --> 00:00:12,840 Center podcast. I'm Jeff, and that's Jim. 3 00:00:12,840 --> 00:00:15,000 Hey, Jim. Hey, Jeff, how are you? 4 00:00:15,280 --> 00:00:16,880 I'm good. I see that sly smile on your 5 00:00:16,880 --> 00:00:19,640 face. It's just I'm very excited for 6 00:00:19,640 --> 00:00:21,960 this episode. We've got a great innovator in 7 00:00:21,960 --> 00:00:25,320 our space here today and I want to jump right into it. 8 00:00:25,320 --> 00:00:27,560 What about you? Yeah, today is a sponsored 9 00:00:27,560 --> 00:00:29,520 episode. So thanks to our friends over at 10 00:00:29,520 --> 00:00:32,360 Exonius and Exonius X. Maybe we'll we'll kind of figure 11 00:00:32,360 --> 00:00:33,560 out what that means here in a second. 12 00:00:33,880 --> 00:00:37,240 But today is all about Exonius and kind of learning what they 13 00:00:37,240 --> 00:00:38,600 come through. These are sponsored episodes 14 00:00:38,600 --> 00:00:41,640 that we do from time to time just to, you know, have be a 15 00:00:41,640 --> 00:00:45,080 little bit more vendor, less vendor neutral than we normally 16 00:00:45,080 --> 00:00:47,760 are in our normal episodes. So, so with that, we've got 17 00:00:47,760 --> 00:00:49,560 Exonius. You can find them on the web, 18 00:00:49,560 --> 00:00:56,960 exonius.com/I DACAXONI, us.com and we've got we've got Omir 19 00:00:56,960 --> 00:00:59,280 Ofek. He's the CEO at Exonius X. 20 00:00:59,280 --> 00:01:02,200 So welcome to the show, Omir. Thanks, Jeff. 21 00:01:02,280 --> 00:01:03,760 Thanks, Jim. Great to be here. 22 00:01:04,280 --> 00:01:05,440 Yeah, thanks for taking the time. 23 00:01:05,440 --> 00:01:08,480 So I, I, I have a couple questions I want to ask you. 24 00:01:08,480 --> 00:01:11,200 I, I'm going to ask you about your background 1st and then 25 00:01:11,200 --> 00:01:12,320 we're going to get into some other things. 26 00:01:12,320 --> 00:01:15,040 So tell us a little bit about how you got into the identity 27 00:01:15,040 --> 00:01:17,480 access management space. Is it something that you chose 28 00:01:17,480 --> 00:01:20,480 or did it choose you? Oh, well, I would say it 29 00:01:20,480 --> 00:01:25,360 definitely chose me kind of. So I, I started my career in, in 30 00:01:25,360 --> 00:01:28,640 cybersecurity way back in the 8200. 31 00:01:28,640 --> 00:01:32,920 There's many Israelis. I didn't did a shift to the IT 32 00:01:32,920 --> 00:01:35,800 world. I'm an IT engineer by profession 33 00:01:35,800 --> 00:01:38,800 and kind of a long career in IT and then came back to 34 00:01:38,800 --> 00:01:42,160 cybersecurity. I was working as ACEO of a few 35 00:01:42,160 --> 00:01:47,360 startups and four years ago I, I joined Axonius to establish 36 00:01:47,360 --> 00:01:50,200 Axonius X and we can speak about that in a bit. 37 00:01:51,280 --> 00:01:55,440 And the first product we actually brought to market was 38 00:01:55,440 --> 00:01:59,640 around SAS management. And during that we actually 39 00:01:59,920 --> 00:02:04,280 encountered a lot of IAM teams that were challenged with 40 00:02:04,520 --> 00:02:09,280 managing SAS, SSPM and so on. And they actually told us and 41 00:02:09,560 --> 00:02:13,000 again, we can go into more details later, they told us, 42 00:02:13,000 --> 00:02:16,560 look, you're already doing all those great things and, and 43 00:02:16,840 --> 00:02:19,320 great value that you bring around SAS applications. 44 00:02:19,320 --> 00:02:22,560 Why don't you actually drive it also with identities? 45 00:02:23,440 --> 00:02:27,160 And that's what kind of got us excited about the, the identity 46 00:02:27,160 --> 00:02:30,760 management domain and we started thinking whether we can actually 47 00:02:30,760 --> 00:02:32,600 create the product in that space. 48 00:02:32,600 --> 00:02:35,000 So that's that's how I got into identities. 49 00:02:35,680 --> 00:02:37,120 So you're kind of preaching the choir here, right? 50 00:02:37,120 --> 00:02:40,320 This is identity at the center. So you know, we're talking 51 00:02:40,320 --> 00:02:42,240 identity. I want to know more about 52 00:02:42,240 --> 00:02:44,680 Exonius. And then I mentioned Exonius X. 53 00:02:45,000 --> 00:02:48,760 What is the difference and what is the X signify I guess? 54 00:02:49,520 --> 00:02:51,960 Yeah. So Exonis has been around for 55 00:02:51,960 --> 00:02:54,560 eight years. It's a it's one of the the 56 00:02:54,560 --> 00:02:57,360 leading unicorns in the cybersecurity space. 57 00:02:58,360 --> 00:03:03,440 The company was founded by Dean Ofreen Avidor over 8 years ago 58 00:03:04,240 --> 00:03:08,160 with the premise of being really a data first company dealing 59 00:03:08,160 --> 00:03:13,200 with data, analyzing data. The first area that the company 60 00:03:13,320 --> 00:03:17,080 ventured into was the asset management space, A category 61 00:03:17,080 --> 00:03:20,600 that there was called Chasm. We didn't kill this category 62 00:03:20,600 --> 00:03:24,160 today is kind of part of C Tam, but really in the asset 63 00:03:24,160 --> 00:03:27,920 management space. And as the as the company 64 00:03:27,920 --> 00:03:32,000 evolved the founders and mainly Dean kind of thought through a 65 00:03:32,000 --> 00:03:36,320 vision of bringing a platform in and he was thinking how is the 66 00:03:36,320 --> 00:03:40,600 best way of of actually doing it by one way could be through 67 00:03:40,600 --> 00:03:43,840 acquisitions and bringing kind of M&A etcetera. 68 00:03:44,000 --> 00:03:46,080 And the other way we could be actually through kind of 69 00:03:46,080 --> 00:03:51,040 internal growth, that's more or less the time where I sold the 70 00:03:51,040 --> 00:03:55,200 company I was CEO of to Rapid 7 and Dean and I knew each other 71 00:03:55,200 --> 00:03:57,600 very well. And he kind of made the right 72 00:03:57,600 --> 00:03:59,680 assumption. I'm not going to stay in the 73 00:03:59,680 --> 00:04:04,120 enterprise world and and kind of do another gig in startup. 74 00:04:04,520 --> 00:04:07,200 And that's kind of when he reached out and said, why don't 75 00:04:07,200 --> 00:04:10,960 we find the structure that can work together doing innovation 76 00:04:10,960 --> 00:04:14,440 from within Exonius. It took us a few days to think 77 00:04:14,440 --> 00:04:18,760 about it and we quickly came to kind of this very innovative, I, 78 00:04:18,760 --> 00:04:23,560 I must say, model of Axonius X, which is really an incubator 79 00:04:23,640 --> 00:04:26,520 from an existing startup. Now back then Axonius was 80 00:04:26,520 --> 00:04:30,320 already kind of growth startup, but still a startup. 81 00:04:30,640 --> 00:04:33,320 And to build kind of an incubation from within is 82 00:04:33,320 --> 00:04:37,240 something that is not trivial. So I joined together with my Co 83 00:04:37,240 --> 00:04:40,880 founders of Axonius X with Rory and Hen and we established this 84 00:04:41,280 --> 00:04:46,080 unique model where we constantly on the lookout for new products, 85 00:04:46,080 --> 00:04:49,880 new areas that we can evolve that Sony's platform into. 86 00:04:50,200 --> 00:04:54,160 And that's kind of what we what we work on. 1st product was in 87 00:04:54,160 --> 00:04:57,400 the SAS management space and our second product is in identity 88 00:04:57,400 --> 00:05:00,640 management. So you mentioned sort of like 89 00:05:00,640 --> 00:05:03,480 asset inventory and we just did an episode where we talked about 90 00:05:03,600 --> 00:05:06,800 attack surface management and identity being part of those 91 00:05:06,800 --> 00:05:08,920 things you need to manage in inventory as well. 92 00:05:09,280 --> 00:05:14,000 Is that the genesis, you know, for this I guess kind of turn 93 00:05:14,000 --> 00:05:15,920 towards things? I mean it seems kind of logical 94 00:05:15,920 --> 00:05:17,720 to me. It's like, OK, we you can only 95 00:05:17,720 --> 00:05:22,480 protect what you know about and sure, laptops hardware, right? 96 00:05:22,480 --> 00:05:24,320 That makes sense. But identities are something you 97 00:05:24,320 --> 00:05:25,200 should know about as well, right? 98 00:05:25,200 --> 00:05:27,520 Is that is that really kind of how this started or was there 99 00:05:27,520 --> 00:05:30,160 something else that drove you to kind of build this solution? 100 00:05:30,760 --> 00:05:34,720 No, this, this is very much it. Now it came from customers, not 101 00:05:34,720 --> 00:05:39,120 from us. So I would say asset, the moment 102 00:05:39,120 --> 00:05:41,920 you, you speak about asset, asset can be various aspects. 103 00:05:41,920 --> 00:05:44,840 So you're right, like they they need a default and asset is a 104 00:05:44,840 --> 00:05:48,440 device, it's a laptop, it's a server, it's a workload and so 105 00:05:48,440 --> 00:05:51,080 on. But four years ago when we 106 00:05:51,080 --> 00:05:54,720 started thinking about our first product in Exonia 6 customers 107 00:05:54,720 --> 00:05:58,240 told us, look, we now have new assets called SAS applications. 108 00:05:58,520 --> 00:06:00,840 We want to treat them. They're kind of beyond our 109 00:06:00,840 --> 00:06:03,120 perimeter. They're not right in our 110 00:06:03,120 --> 00:06:04,960 control. This is something we need to 111 00:06:04,960 --> 00:06:06,720 manage. We need to treat it like another 112 00:06:06,720 --> 00:06:10,000 asset from configuration perspective, usage perspective, 113 00:06:10,000 --> 00:06:13,000 users perspective and so on. And that's kind of what got us 114 00:06:13,120 --> 00:06:15,920 into dealing with SAS as another asset. 115 00:06:16,240 --> 00:06:19,280 And then customers told us, wait, you're already dealing 116 00:06:19,280 --> 00:06:21,240 with SAS. Now there is another asset 117 00:06:21,240 --> 00:06:23,960 exactly like you said, Jeff, which is identities, which is 118 00:06:23,960 --> 00:06:25,600 becoming more and more important. 119 00:06:26,040 --> 00:06:30,080 We need to treat our identities as another asset inventory that 120 00:06:30,080 --> 00:06:33,040 we have in the company. We need to have full visibility 121 00:06:33,200 --> 00:06:36,240 on all of the identities that we have, whether they're non human, 122 00:06:36,240 --> 00:06:39,520 whether they're human, whether they're on Prem, whether they're 123 00:06:39,520 --> 00:06:42,840 SAS, whether they're on cloud. And we need to treat them as if 124 00:06:42,840 --> 00:06:46,800 there were another asset that is important to manage, important 125 00:06:46,800 --> 00:06:51,000 to see the usage of and so on. So absolutely, the way we see 126 00:06:51,120 --> 00:06:54,680 identity is yet another asset that the company needs to manage 127 00:06:55,360 --> 00:06:58,280 and that's what customers told us and that's what we are doing. 128 00:06:59,600 --> 00:07:03,480 So I'm always fascinated by the naming of companies, and Exonius 129 00:07:03,480 --> 00:07:07,160 is pretty unique. Tell me about how you know, what 130 00:07:07,160 --> 00:07:09,200 does the name mean? Does it doesn't mean anything? 131 00:07:09,760 --> 00:07:12,160 How did you come up with the name Exonius for the company? 132 00:07:12,560 --> 00:07:14,640 Yeah, so, so I did not come up with the name. 133 00:07:15,160 --> 00:07:17,440 It's the founders that came up with the name. 134 00:07:17,640 --> 00:07:21,600 And actually Exonius is well, they thought of of a name that 135 00:07:21,600 --> 00:07:24,840 starts with a. So that was one of the one of 136 00:07:24,840 --> 00:07:27,480 the first parameters and then they thought of a certain 137 00:07:27,480 --> 00:07:28,840 section. Actually, as you can see in the 138 00:07:28,840 --> 00:07:34,200 logo is actually a practical in the neuro system that connects 139 00:07:34,200 --> 00:07:38,160 between different areas of the neuro system axiom. 140 00:07:38,200 --> 00:07:42,000 So this is actually kind of the connection of the first axioms. 141 00:07:42,000 --> 00:07:44,920 So that's how the name and that's what we do in Exonius. 142 00:07:44,920 --> 00:07:48,640 We actually connect data, we connect information, we connect 143 00:07:48,640 --> 00:07:52,360 information from multiple sources to become this kind of 144 00:07:52,640 --> 00:07:55,360 nervous system sort of speak of the organization. 145 00:07:55,840 --> 00:07:58,000 I love that that's such a good little like Easter egg for 146 00:07:58,000 --> 00:07:59,640 people who aren't familiar, like neurons. 147 00:07:59,760 --> 00:08:00,760 And. Stuff like that. 148 00:08:00,760 --> 00:08:02,880 Yeah, that's a great way to like, you know, put it. 149 00:08:03,520 --> 00:08:07,560 So you're in this space that Gartner is calling IVIP or make 150 00:08:07,560 --> 00:08:09,600 sure I get it right. Identity visibility 151 00:08:09,600 --> 00:08:12,680 infrastructure platform. So tell me about this 152 00:08:12,840 --> 00:08:15,440 intelligence. Identity visibility 153 00:08:15,440 --> 00:08:17,520 intelligence. OK, intelligence. 154 00:08:17,520 --> 00:08:19,720 So thank you for correcting me. It's new, new to me. 155 00:08:19,720 --> 00:08:21,800 I had not heard about this until, you know, just recently. 156 00:08:21,800 --> 00:08:24,960 So IVIP identity visibility intelligence platform. 157 00:08:25,440 --> 00:08:28,240 What is that space? And then I guess you know, the, 158 00:08:28,480 --> 00:08:31,160 the, the $1,000,000 question is what is it that makes you guys 159 00:08:31,160 --> 00:08:33,799 different in that space? Or maybe some other vendors that 160 00:08:33,799 --> 00:08:34,960 might be playing in the same area? 161 00:08:35,679 --> 00:08:37,640 Absolutely. So it is brand new. 162 00:08:38,080 --> 00:08:43,679 It just came up in the very recent I digital identity hype 163 00:08:43,679 --> 00:08:46,640 cycle that Gartner released in in July. 164 00:08:46,920 --> 00:08:51,040 So it's very, very new. And this new category I guess is 165 00:08:51,040 --> 00:08:54,040 is some of a symptom that we see today in general in the in the 166 00:08:54,040 --> 00:08:58,160 identity or IGA space. So over the last, I would say 167 00:08:58,400 --> 00:09:02,320 year or two, we we started seeing a lot of bespoke 168 00:09:02,320 --> 00:09:05,600 categories that are kind of breaking the traditional IGA. 169 00:09:05,760 --> 00:09:09,520 We start seeing NHI as a new category, we start seeing ITVR 170 00:09:09,520 --> 00:09:12,720 as a separate category. We start seeing ISPN as another 171 00:09:12,720 --> 00:09:15,120 category. And I think that actually 172 00:09:15,120 --> 00:09:18,480 demonstrate the fact that the IGA world is now going through 173 00:09:18,480 --> 00:09:21,000 some disruption or some transformation. 174 00:09:21,920 --> 00:09:26,600 The area that Gartner identified as Ivy is really around bringing 175 00:09:26,600 --> 00:09:29,520 visibility and intelligence into identity. 176 00:09:29,800 --> 00:09:33,040 So it's clear today that identity resides in many, many 177 00:09:33,040 --> 00:09:36,160 silos in many, many areas of the organization. 178 00:09:36,560 --> 00:09:40,200 It's no longer a monolithic environment that you can have 179 00:09:40,560 --> 00:09:44,480 all of your identities managed on your single AD or your single 180 00:09:44,480 --> 00:09:46,800 SAP. And that's why visibility is 181 00:09:46,800 --> 00:09:50,640 becoming so much more important because identities, permissions, 182 00:09:50,640 --> 00:09:52,320 entitlements, today they reside everywhere. 183 00:09:52,520 --> 00:09:56,880 And unless you have very profound, very broad visibility 184 00:09:56,920 --> 00:10:00,200 of the entire organization, the entire pockets of where identity 185 00:10:00,200 --> 00:10:03,520 resides, you, you're always missing out on something. 186 00:10:03,520 --> 00:10:06,320 And then if you don't see, you cannot actually manage it. 187 00:10:06,600 --> 00:10:08,760 And that's why the visibility part is important. 188 00:10:08,800 --> 00:10:13,040 But what Gartner actually very wisely did is they aligned it 189 00:10:13,040 --> 00:10:15,840 with what they call intelligence, which is the 190 00:10:15,840 --> 00:10:18,800 visibility by itself is not. It's good, but it's only a first 191 00:10:18,800 --> 00:10:20,720 step. You need to make sense of what 192 00:10:20,720 --> 00:10:22,680 you're seeing. You need to make sense of the 193 00:10:22,680 --> 00:10:26,000 context of those permissions. For example, you need to make 194 00:10:26,000 --> 00:10:29,720 sense of how a single permission is connected to another one, how 195 00:10:29,720 --> 00:10:32,720 you can cluster them together, how you can do a much more 196 00:10:32,720 --> 00:10:37,480 profound role mining, how you can come with much more a smart 197 00:10:37,520 --> 00:10:41,080 analytics and, and maybe kind of use of AI in terms of 198 00:10:41,080 --> 00:10:44,360 recommending, of roles of recommending, of functionality. 199 00:10:44,560 --> 00:10:46,680 And that's exactly what we do in Exonia. 200 00:10:46,680 --> 00:10:49,760 So as I mentioned in Exonia's, we're all about data. 201 00:10:49,760 --> 00:10:54,600 First we bring the identity data into one single place creating 202 00:10:54,600 --> 00:10:57,600 one visibility. But then we are able to actually 203 00:10:57,600 --> 00:11:01,360 go to the granularity of this data and drive analysis and 204 00:11:01,360 --> 00:11:05,920 smart recommendations, mark actions from what we are 205 00:11:05,920 --> 00:11:10,960 gathering in order to make sense of your entire identity life 206 00:11:10,960 --> 00:11:14,640 cycle. Unlike other maybe players in 207 00:11:14,640 --> 00:11:19,680 this category, we also evolved from IVIP into proper IGA. 208 00:11:19,960 --> 00:11:25,000 So we don't see kind of IGA as a as a kind of a separate area. 209 00:11:25,000 --> 00:11:28,040 We think that through visibility you can actually manage much 210 00:11:28,040 --> 00:11:32,040 better your IGA program, your IGA capabilities. 211 00:11:32,040 --> 00:11:36,080 And within our product, we also have like the bread and butter 212 00:11:36,080 --> 00:11:40,960 or the core functionality of IGA, like access reviews, like a 213 00:11:40,960 --> 00:11:45,000 role mining, like identity life cycle management and so on. 214 00:11:46,520 --> 00:11:49,120 So Amir, I'd like to get into the products a little bit. 215 00:11:49,160 --> 00:11:52,360 And first thing I'd like to understand is kind of the why. 216 00:11:52,640 --> 00:11:58,720 So why do organizations find themselves leading the Exonius 217 00:11:58,720 --> 00:12:00,440 products? What is the problem that they're 218 00:12:00,440 --> 00:12:03,840 trying to solve? I think I think the first 219 00:12:03,840 --> 00:12:07,520 problem that we saw actually I would say two the first problem 220 00:12:07,520 --> 00:12:10,640 that we saw is, is around this visibility and the fact that 221 00:12:10,640 --> 00:12:14,680 today there is all of those silos of identity in the 222 00:12:14,680 --> 00:12:17,000 organization. The more organizations are 223 00:12:17,000 --> 00:12:21,680 becoming complex from cloud deployment, from SAS deployment, 224 00:12:21,880 --> 00:12:25,800 even sometimes even just with on Prem multiple ADS that are 225 00:12:25,800 --> 00:12:29,040 sprawling M And as that companies are doing, all of a 226 00:12:29,040 --> 00:12:31,880 sudden there is identity that resides in so many different 227 00:12:31,880 --> 00:12:36,320 places, entitlements that are spreading around non human 228 00:12:36,320 --> 00:12:38,720 identities that are becoming more and more and more 229 00:12:38,720 --> 00:12:42,000 important. And organizations are losing 230 00:12:42,000 --> 00:12:46,280 track or or losing ability to capture all of the identity that 231 00:12:46,280 --> 00:12:49,120 they have. So the first really challenge 232 00:12:49,120 --> 00:12:52,600 that we come to solve is creating that single visibility 233 00:12:52,840 --> 00:12:55,760 from any source that you have identity residing in. 234 00:12:55,960 --> 00:12:57,880 And that's kind of what we know how to do in Exonics. 235 00:12:58,080 --> 00:13:00,840 Exonics we know to connect to any data source. 236 00:13:00,840 --> 00:13:06,040 We have today over 1200 off the shelf integrations, we call them 237 00:13:06,040 --> 00:13:08,320 adapters. We know how to correlate them, 238 00:13:08,600 --> 00:13:12,440 to duplicate them, align them into what we call this adapter 239 00:13:12,440 --> 00:13:14,880 network under a single data model. 240 00:13:15,320 --> 00:13:18,800 And then you get basically a single identity store where you 241 00:13:18,800 --> 00:13:21,160 can start driving analysis and actions from. 242 00:13:21,360 --> 00:13:24,800 So the first challenge is really this visibility challenge of 243 00:13:24,840 --> 00:13:27,400 aggregating all of the identity into one place. 244 00:13:27,720 --> 00:13:31,400 The second one which is slightly tied to that is the time to 245 00:13:31,400 --> 00:13:34,520 value. We see with traditional IGA 246 00:13:34,920 --> 00:13:38,800 solutions out there time to value is something that these is 247 00:13:38,800 --> 00:13:43,360 really mind boggling today. You know an IGA program can run 248 00:13:43,360 --> 00:13:47,960 12 months, 18 months, 30. I heard you know even 36 months 249 00:13:47,960 --> 00:13:51,480 as being very, very common. We want to narrow that down. 250 00:13:51,600 --> 00:13:56,440 We want to enable an IM practitioner to be able to drive 251 00:13:56,720 --> 00:14:01,040 strong solid recommendations on what should be, it's a 252 00:14:01,160 --> 00:14:05,520 birthright rules on what should be the mover rules on the lever 253 00:14:05,520 --> 00:14:09,240 side of things, on assigning gay owners to non human accounts and 254 00:14:09,240 --> 00:14:12,960 so on within a matter of weeks, not within a matter of months. 255 00:14:13,440 --> 00:14:17,840 And our ability to narrow down that timeline is driven first 256 00:14:17,840 --> 00:14:21,640 because of those integrations. So we, we don't need to spend 257 00:14:22,000 --> 00:14:25,280 month and month of building customized integrations and and 258 00:14:25,280 --> 00:14:28,040 connections etcetera. We already have them available. 259 00:14:28,200 --> 00:14:32,680 We already correlate them and align them in single data place 260 00:14:32,840 --> 00:14:36,000 that narrows down by a lot. And the second thing is by 261 00:14:36,000 --> 00:14:39,760 applying smart AI that can come actually with very solid 262 00:14:39,760 --> 00:14:43,200 recommendations upfront. And by that we we actually 263 00:14:43,200 --> 00:14:45,480 reduced substantially the time to value. 264 00:14:46,960 --> 00:14:51,200 That second part about the time to value is that's an awesome 265 00:14:51,200 --> 00:14:53,760 selling plate. But I got to tell you as a 266 00:14:53,760 --> 00:14:57,600 identity practitioner, the first point that you brought up was 267 00:14:57,600 --> 00:14:59,920 really to me like what resonates? 268 00:14:59,920 --> 00:15:04,280 You need to have one place to go to know who has access to what. 269 00:15:04,560 --> 00:15:08,720 I think you're looking at it from a unique perspective, which 270 00:15:08,720 --> 00:15:12,960 is really hyper fixating on these, on the data. 271 00:15:13,400 --> 00:15:16,360 And so maybe you could dive into that a little bit further. 272 00:15:16,360 --> 00:15:19,760 What what is it that you keep talking about data being so 273 00:15:19,760 --> 00:15:22,520 important? Help us understand why. 274 00:15:22,520 --> 00:15:27,000 Why is that the perspective? Yeah, I think at the end of the 275 00:15:27,000 --> 00:15:30,680 day, there's maybe in high level two ways of looking at the IGA. 276 00:15:30,680 --> 00:15:35,080 1 can be more of a process oriented way of putting in place 277 00:15:35,080 --> 00:15:37,720 kind of a procedures and processes in the in the 278 00:15:37,720 --> 00:15:40,400 organization. The other one is is data-driven. 279 00:15:40,440 --> 00:15:44,760 The reason I think data is the more important one is because at 280 00:15:44,760 --> 00:15:48,040 the end of the day you can collect a lot of you can drive a 281 00:15:48,040 --> 00:15:51,560 lot of processes around the identity policies and so on. 282 00:15:51,560 --> 00:15:55,840 But if you don't collect the right information, the right 283 00:15:55,840 --> 00:16:01,560 data, for example, to the level of resource level, granularity 284 00:16:01,560 --> 00:16:06,920 of permissions and entitlement, whether Jim has a permission to 285 00:16:06,920 --> 00:16:12,600 access a GitHub repo that Jeff is not allowed to to access. 286 00:16:12,880 --> 00:16:16,320 This level of granularity of of access, of entitlement, of 287 00:16:16,320 --> 00:16:21,600 permission is very important to first have a comprehensive view 288 00:16:21,600 --> 00:16:23,840 of it. So you need to know of all of 289 00:16:23,840 --> 00:16:25,760 the permissions, all the entitlements that exist in the 290 00:16:25,760 --> 00:16:28,440 organization. And secondly, you need to make 291 00:16:28,440 --> 00:16:30,400 sense out of it in in the right context. 292 00:16:30,400 --> 00:16:34,440 So you need to make sure that the permissions are being 293 00:16:35,120 --> 00:16:39,000 aligned, entitlements are being aligned and it all stems from 294 00:16:39,000 --> 00:16:42,880 from a data perspective and not so much from whether you have 295 00:16:42,880 --> 00:16:46,240 the right kind of, I don't know, policy in the organization to 296 00:16:46,960 --> 00:16:50,600 give the employees access at the moment they join the company. 297 00:16:51,920 --> 00:16:55,080 The other aspect is that with a lot of companies, we find a lot 298 00:16:55,080 --> 00:16:57,440 of historical information that that resides. 299 00:16:57,440 --> 00:17:01,080 So companies accumulate throughout the years a lot of 300 00:17:01,320 --> 00:17:08,160 rules and policies, a lot of garbage groups in ADA, lot of, 301 00:17:08,599 --> 00:17:11,839 you know, provisions that are not even in use in the company. 302 00:17:12,200 --> 00:17:16,480 So in order to drive something that I, I think is a lot, a lot 303 00:17:16,520 --> 00:17:20,240 kind of forgotten a lot to drive identity hygiene, you need to 304 00:17:20,240 --> 00:17:24,079 have proper data and, and you need to constantly make sure 305 00:17:24,079 --> 00:17:26,800 that the data is, is, is in good hygiene mode. 306 00:17:27,119 --> 00:17:30,200 And this is something a lot of IAM teams are neglecting, 307 00:17:30,480 --> 00:17:33,040 unfortunately, because it's a very kind of maintain task to 308 00:17:33,040 --> 00:17:36,280 just go over all of the groups constantly and clean them up and 309 00:17:36,280 --> 00:17:38,880 make sure that the roles are right size and, and so on. 310 00:17:39,200 --> 00:17:43,400 But if you accumulate all of that dust or garbage over time, 311 00:17:43,640 --> 00:17:46,280 then you, you don't see what you really need to see. 312 00:17:46,400 --> 00:17:48,480 You don't see the real roles that you need to manage. 313 00:17:48,480 --> 00:17:51,080 You don't see the real permissions that are faulty. 314 00:17:52,000 --> 00:17:54,640 And I think that you can only achieve when you get the data 315 00:17:54,640 --> 00:17:57,560 right? No, that really resonates with 316 00:17:57,560 --> 00:17:59,360 me. I mean, we've always said 317 00:17:59,360 --> 00:18:03,680 garbage in, garbage out. I know that identity 318 00:18:03,680 --> 00:18:06,520 practitioners are doing their best if they need to have the 319 00:18:06,520 --> 00:18:09,720 tools to make it so that it's scalable. 320 00:18:09,720 --> 00:18:14,360 Because the the issue that you're bringing up is that 321 00:18:14,360 --> 00:18:18,280 there's just too much to do bottom line, that if you don't 322 00:18:18,280 --> 00:18:21,760 have the automation, you don't have the tools, how can you be 323 00:18:21,760 --> 00:18:26,520 expected to succeed That you earlier brought up something 324 00:18:26,520 --> 00:18:29,680 else that you know, a lot of different things are happening 325 00:18:30,080 --> 00:18:32,400 within the industry and people are trying to bring different 326 00:18:32,400 --> 00:18:35,000 flavours. You've run up the non human 327 00:18:35,000 --> 00:18:39,840 identity part of the story, which really resonates me and 328 00:18:39,840 --> 00:18:41,760 Jeff, we've talked about it a lot. 329 00:18:42,480 --> 00:18:46,920 You know, non human identities is not really a brand new story. 330 00:18:47,120 --> 00:18:50,800 And you know, we started in this industry over 20 years ago. 331 00:18:51,040 --> 00:18:54,720 We're still dealing with non human identities, but now it's 332 00:18:54,720 --> 00:18:59,240 gotten to the point that it's expanding so much. 333 00:18:59,960 --> 00:19:03,840 You mentioned workloads, devices, everything's got 334 00:19:04,080 --> 00:19:07,920 identities now, so it's a bigger problem. 335 00:19:08,120 --> 00:19:14,920 And these non human identities are often harder to secure with 336 00:19:14,920 --> 00:19:17,200 like multi factor authentication, things like 337 00:19:17,200 --> 00:19:20,280 that. That's a big lead in for a very 338 00:19:20,280 --> 00:19:26,400 simple question, which is, from your focus, what kind of 339 00:19:26,400 --> 00:19:30,040 accounts does this visibility matter the most for? 340 00:19:30,240 --> 00:19:34,440 Is it the humans, is it the non humans, or is it really both? 341 00:19:34,440 --> 00:19:36,880 Or should they be looked at almost equally? 342 00:19:37,560 --> 00:19:40,200 It's both. I I I think that there should 343 00:19:40,200 --> 00:19:43,360 not be discrimination in general between humans. 344 00:19:43,680 --> 00:19:46,640 So I think there's also should not be discrimination between 345 00:19:46,640 --> 00:19:49,720 humans and non humans. If we look at the organization 346 00:19:49,720 --> 00:19:54,320 down the road, let's say let's take kind of a leap of faith 20 347 00:19:54,320 --> 00:19:57,280 years down the road, at the end of the day, you'll have a lot of 348 00:19:57,600 --> 00:20:01,680 AIAI agents roaming around. You'll have a lot of service 349 00:20:01,680 --> 00:20:03,280 accounts. Everything will be in service 350 00:20:03,280 --> 00:20:06,120 accounts in my mind. And you'll have some humans, but 351 00:20:06,200 --> 00:20:09,400 they will all need to be treated more or less the same way. 352 00:20:09,440 --> 00:20:11,480 Of course, they will have different traits and different 353 00:20:11,480 --> 00:20:14,160 behavior and so on. But from an identity 354 00:20:14,160 --> 00:20:16,360 perspective, if you look at the company. 355 00:20:17,040 --> 00:20:20,480 The identities in the company will be those agents, they will 356 00:20:20,480 --> 00:20:23,520 behave like employees. You know, they, they will drive 357 00:20:23,520 --> 00:20:26,680 decisions, they will drive automation, they will drive 358 00:20:26,680 --> 00:20:30,080 maybe a lot of the functionality of the, you know, of the service 359 00:20:30,080 --> 00:20:32,680 that the company provide. You will have, of course, 360 00:20:32,680 --> 00:20:38,000 humans, sprinkle of humans and, and you'll have and you'll have 361 00:20:38,360 --> 00:20:41,160 non human identities, service accounts that they all of those 362 00:20:41,160 --> 00:20:43,160 humans will be managing and so on. 363 00:20:43,440 --> 00:20:46,080 So you cannot really kind of discriminate between 1:00 or 364 00:20:46,080 --> 00:20:47,960 another. At the end of the day, all of 365 00:20:47,960 --> 00:20:50,640 those are identities. And the shift we're seeing by 366 00:20:50,640 --> 00:20:55,560 the way, today of security to be kind of identity first is all 367 00:20:55,560 --> 00:20:58,720 driven by that because at the end of the day, to protect the 368 00:20:58,720 --> 00:21:02,600 organization, you need to protect the people or the 369 00:21:02,840 --> 00:21:07,320 machines that have access to data and you need to treat them 370 00:21:07,320 --> 00:21:10,520 the same way. So that's why our philosophy is 371 00:21:10,520 --> 00:21:14,320 that you need to aggregate all data, whether it is of a service 372 00:21:14,320 --> 00:21:17,080 account and making sure that you know who's the owner of that 373 00:21:17,080 --> 00:21:19,600 service account and what permission this service account 374 00:21:19,600 --> 00:21:24,360 has, whether it is a human information, which is easily 375 00:21:24,360 --> 00:21:27,680 maybe getting information from your IDP. 376 00:21:27,680 --> 00:21:31,680 Yeah, MFA is very much kind of relevant source of information, 377 00:21:31,680 --> 00:21:36,360 source of a of a mean to manage human accounts and all the way 378 00:21:36,360 --> 00:21:40,240 to maybe a gentic AI and how those kind of sprawl around. 379 00:21:40,240 --> 00:21:42,920 You need to bring all of that information one single place. 380 00:21:43,360 --> 00:21:46,680 And of course for each one try to drive different actions and 381 00:21:46,680 --> 00:21:50,640 different maybe automation on on kind of monitoring or 382 00:21:50,640 --> 00:21:54,560 protecting, but it all needs to be treated from from same 383 00:21:54,560 --> 00:21:57,360 perspective. You cannot say you're going to 384 00:21:57,360 --> 00:22:03,000 silo that. So that's a great overview on 385 00:22:03,040 --> 00:22:09,400 why Axonius was built, why customers might want to use this 386 00:22:09,400 --> 00:22:14,160 tool in their environment. Just talk about how so identity, 387 00:22:14,160 --> 00:22:19,960 visibility and intelligence. How does Axonius make the 388 00:22:19,960 --> 00:22:23,720 visibility piece happen? Yeah. 389 00:22:23,720 --> 00:22:27,880 So from our perspective, it's relatively straightforward. 390 00:22:28,000 --> 00:22:30,920 The first thing that you do with Axonius is that you connect to 391 00:22:30,920 --> 00:22:34,800 sources of data. Axonius is not about deploying 392 00:22:34,800 --> 00:22:40,320 another scanner or another agent or another kind of a tool that 393 00:22:40,320 --> 00:22:45,080 they will drive kind of an additional, additional discovery 394 00:22:45,080 --> 00:22:47,760 proactively. The way we do the discovery is 395 00:22:47,760 --> 00:22:50,400 actually leveraging already the investment that was made in 396 00:22:50,400 --> 00:22:52,760 other tools. So we would connect to your AD, 397 00:22:52,760 --> 00:22:55,920 we would connect to your Octa, we would connect to your AWS, 398 00:22:55,920 --> 00:23:01,280 your GCP, your Azure, your sales force, your success factor, your 399 00:23:02,040 --> 00:23:04,920 you name it. Any application that has some 400 00:23:04,920 --> 00:23:09,440 aspect of identity to it, we drive those connectors through 401 00:23:09,640 --> 00:23:12,320 what we call adapters. Most of them already we have 402 00:23:12,320 --> 00:23:14,920 out-of-the-box. So it's basically just putting 403 00:23:14,920 --> 00:23:18,480 in place the integration with API and you get, you get that in 404 00:23:18,840 --> 00:23:22,120 and from the moment you connect those adapters, you already have 405 00:23:22,120 --> 00:23:26,280 in our database, in our data model, all of the information 406 00:23:26,360 --> 00:23:29,760 within kind of a matter of a fetch cycle. 407 00:23:29,800 --> 00:23:33,760 So it could be as short as 15 minutes or 24 hours depending on 408 00:23:33,760 --> 00:23:37,640 the on the fetch time. And from that point onwards you 409 00:23:37,640 --> 00:23:40,080 can actually start driving decisions. 410 00:23:40,480 --> 00:23:44,800 You can first see any kind of anomalies that you see in terms 411 00:23:44,800 --> 00:23:49,880 of maybe administrative permissions that should not be 412 00:23:50,080 --> 00:23:53,440 having access. So like excessive permissions 413 00:23:53,440 --> 00:23:55,680 that they were given to some of your admins. 414 00:23:55,920 --> 00:24:00,560 You can see for example, anomalies say entitlements that 415 00:24:00,560 --> 00:24:02,520 were given compared to different groups. 416 00:24:02,920 --> 00:24:06,320 You can start driving decisions by right sizing the roles that 417 00:24:06,320 --> 00:24:10,040 you have in the company. You can actually drive this 418 00:24:10,040 --> 00:24:13,200 hygiene factor that I mentioned in terms of removing of sale 419 00:24:13,200 --> 00:24:15,520 accounts. You can make sure that you have 420 00:24:15,520 --> 00:24:18,240 ownership to all of those non human accounts. 421 00:24:18,720 --> 00:24:23,080 A very common use case, and that is, is now maybe top of the of 422 00:24:23,080 --> 00:24:28,200 the hour given the Cyber Ark acquisition by by Palo Alto is, 423 00:24:28,200 --> 00:24:32,480 is pen making your pen actually much more up to date. 424 00:24:32,840 --> 00:24:35,320 We can help you do that. We can help you make sure that 425 00:24:35,600 --> 00:24:39,400 all of your privileged accounts are the right ones. 426 00:24:39,560 --> 00:24:42,480 All of them are actually configured in your Pam and we 427 00:24:42,480 --> 00:24:45,560 can make sure that the Pam doesn't have any noise of 428 00:24:46,040 --> 00:24:49,240 accounts that are no longer privileged or no longer existing 429 00:24:49,240 --> 00:24:51,960 in the company. So we can make sure your Pam is 430 00:24:51,960 --> 00:24:55,160 always up to date. We have those various use cases 431 00:24:55,600 --> 00:24:58,240 that you can actually start driving that's kind of more from 432 00:24:58,240 --> 00:25:01,000 a visibility perspective and hygiene perspective. 433 00:25:01,320 --> 00:25:04,800 Once you have the hygiene part kind of I wouldn't say sorted 434 00:25:04,800 --> 00:25:08,320 out because it's a never ending task, but in a good, good stage, 435 00:25:08,560 --> 00:25:11,560 then you can actually go to the next layer of driving in my 436 00:25:11,560 --> 00:25:16,480 mind, kind of proper IGA coming with recommendation, leveraging 437 00:25:17,040 --> 00:25:20,400 our machine learning AI, recommending which rules you 438 00:25:20,400 --> 00:25:23,680 need to apply in the company in terms of birthright rules, in 439 00:25:23,680 --> 00:25:26,560 terms of lever rules, in terms of mover rules and so on. 440 00:25:26,720 --> 00:25:29,200 So we can come with our recommendation. 441 00:25:29,440 --> 00:25:33,280 You can actually start doing it by your own IM team that they 442 00:25:33,280 --> 00:25:35,680 will start managing the identity life cycle there. 443 00:25:36,160 --> 00:25:39,880 And you can constantly monitor that you don't have any gaps in 444 00:25:39,880 --> 00:25:45,680 terms of like potential misbehavior, let's say of a of a 445 00:25:46,200 --> 00:25:48,400 non human accounts or human accounts. 446 00:25:48,560 --> 00:25:53,200 So we have constantly tracking of detection of, of, of the 447 00:25:53,280 --> 00:25:57,080 behavior of the, of identities to highlight any kind of 448 00:25:57,720 --> 00:26:00,520 malicious activity or abnormal activities. 449 00:26:00,720 --> 00:26:03,120 So that's kind of the ongoing monitoring of things. 450 00:26:03,840 --> 00:26:07,080 Yeah. And that aspect, just, I get 451 00:26:07,080 --> 00:26:10,960 excited about that the, it almost sounds like user behavior 452 00:26:10,960 --> 00:26:14,840 analytics, which I think I have this moment in the sun. 453 00:26:15,840 --> 00:26:19,440 There were some implementation challenges with it, but to me, 454 00:26:19,440 --> 00:26:23,200 it always made a lot of sense, especially now with the advances 455 00:26:23,200 --> 00:26:25,880 we're seeing in AI and machine learning. 456 00:26:26,720 --> 00:26:31,680 Talk to us a little bit about what XO News brings to the table 457 00:26:31,680 --> 00:26:34,880 in terms of like spotting the abnormal behavior. 458 00:26:35,520 --> 00:26:37,920 Yeah. So we have our own beta 459 00:26:37,920 --> 00:26:42,720 scientist team that developed a few algorithms around machine 460 00:26:42,720 --> 00:26:45,720 learning and we have a few areas in the product that we apply 461 00:26:45,720 --> 00:26:47,800 them. So one kind of the most trivial 462 00:26:47,800 --> 00:26:50,880 one, as I mentioned is around role mining, for example, which 463 00:26:50,880 --> 00:26:55,720 is relatively simple case. It's all about having the right 464 00:26:55,720 --> 00:26:59,280 data before you apply the ML. So if you don't have like cleans 465 00:26:59,280 --> 00:27:03,040 data and the aligned data doesn't matter how good your, 466 00:27:03,040 --> 00:27:05,680 your ML algorithm is it, it will just fail. 467 00:27:06,040 --> 00:27:10,360 Second one is really by applying kind of recommendation of rules 468 00:27:10,360 --> 00:27:12,960 and policies. And that's again something that 469 00:27:12,960 --> 00:27:18,200 we do both using kind of ML and as well as also using a bedrock 470 00:27:18,520 --> 00:27:22,200 for kind of the LLM part of it. And that's kind of more in the 471 00:27:22,200 --> 00:27:25,360 recommendation of policies. And the last piece is really 472 00:27:25,360 --> 00:27:31,240 kind of monitoring the behavior. So you're right that the user 473 00:27:31,240 --> 00:27:33,640 behavior is something that is not new. 474 00:27:34,440 --> 00:27:38,520 I believe that today the technology and the tools that 475 00:27:38,520 --> 00:27:43,000 exist out there enable it to be much more, I guess effective in 476 00:27:43,000 --> 00:27:47,040 terms of the balance between the amount of data that you need to 477 00:27:47,040 --> 00:27:51,200 collect versus the analysis that drive some meaningful analysis. 478 00:27:51,400 --> 00:27:55,240 And I think today we, we reach some sort of a balance that you 479 00:27:55,240 --> 00:27:58,880 don't need to collect endless infinite amount of data in order 480 00:27:58,880 --> 00:28:02,480 for the results to make sense. You can actually drive the 481 00:28:02,480 --> 00:28:06,320 baseline relatively straightforward in a, in a sense 482 00:28:06,320 --> 00:28:12,640 of, I would say a few weeks of, of data consumption driving some 483 00:28:12,640 --> 00:28:16,120 references or kind of referring from traits that you're seeing 484 00:28:16,120 --> 00:28:18,680 in as to what the baseline should look like. 485 00:28:18,680 --> 00:28:23,440 So there's a lot of inferring of data to kind of almost predict 486 00:28:23,680 --> 00:28:25,840 what kind of the the baseline looks like. 487 00:28:26,080 --> 00:28:29,280 And then based on that, you can start kind of highlighting, 488 00:28:29,720 --> 00:28:32,520 highlighting abnormal behavior. And of course, you need to 489 00:28:32,520 --> 00:28:38,480 constantly kind of train the model that that it can can learn 490 00:28:38,720 --> 00:28:41,240 that it's on the right path or wrong path or wrong path. 491 00:28:41,240 --> 00:28:44,520 And the models today really know how to train themselves much 492 00:28:44,520 --> 00:28:47,960 more effectively and much better than I guess they did a decade 493 00:28:47,960 --> 00:28:50,120 ago. So I think from that 494 00:28:50,120 --> 00:28:53,600 perspective, you're reaching kind of a point where the amount 495 00:28:53,600 --> 00:28:56,640 of data that you need to collect versus the output that is 496 00:28:56,880 --> 00:29:00,880 precise and not just creating noise is becoming effective and 497 00:29:00,880 --> 00:29:04,720 efficient that that that was not the case many years. 498 00:29:04,800 --> 00:29:06,240 Ago. Oh, yeah, it's like you read my 499 00:29:06,240 --> 00:29:08,640 mind because that's really what I was talking about when it came 500 00:29:08,640 --> 00:29:14,360 to challenges was in the past, it seemed to me like use of 501 00:29:14,360 --> 00:29:19,720 behavior just required tons of data to the point of almost for 502 00:29:19,720 --> 00:29:23,600 some organizations being unrealistic, the amount of data. 503 00:29:23,720 --> 00:29:28,600 So it sounds to me like if I heard you right, it's well we 504 00:29:28,600 --> 00:29:34,280 need, I think you said a couple of weeks, maybe a month of data 505 00:29:34,720 --> 00:29:39,040 and then it's about having the precision of the data, right, 506 00:29:39,040 --> 00:29:41,920 not just getting data for the sake of having data. 507 00:29:42,040 --> 00:29:45,240 Exactly, exactly. I think what we know what to do 508 00:29:45,240 --> 00:29:47,800 very well in Exonius, but I think it's it's also general 509 00:29:47,800 --> 00:29:52,240 today is to collect the right data points that can infer of of 510 00:29:52,280 --> 00:29:53,400 patterns. OK. 511 00:29:53,720 --> 00:29:57,040 So it's not like in the past that you collected barrages of 512 00:29:57,040 --> 00:30:00,640 data and then kind of start applying a lot of cleansing on 513 00:30:00,640 --> 00:30:03,480 it and so on. Today you really know how to 514 00:30:03,480 --> 00:30:07,760 choose what are the data points within the logs, within maybe 515 00:30:07,760 --> 00:30:11,880 the permission attributes, within the user attributes, What 516 00:30:11,880 --> 00:30:14,040 are the data points that are actually going to be most 517 00:30:14,040 --> 00:30:19,640 significant to infer what is that kind of state status or 518 00:30:19,640 --> 00:30:25,720 like the the baseline state. And from that derive what, 519 00:30:25,720 --> 00:30:28,080 what's kind of the anomalous behavior. 520 00:30:28,320 --> 00:30:32,120 So it's it's much less logs, much less data that you need to 521 00:30:32,120 --> 00:30:33,240 actually. Pick. 522 00:30:34,240 --> 00:30:37,040 Yeah, I do want to clarify that. So when you talk about data, 523 00:30:37,040 --> 00:30:39,040 you're talking about log data, right? 524 00:30:39,040 --> 00:30:40,840 You're you're talking about collecting logs. 525 00:30:41,040 --> 00:30:45,240 What are the the typical kind of systems that you're grabbing the 526 00:30:45,240 --> 00:30:46,840 logs from? Yeah. 527 00:30:46,840 --> 00:30:50,040 So it's not only logs, not only logs, it's a mixture of. 528 00:30:50,040 --> 00:30:55,400 So if we speak about logs for behavior usage, it would be like 529 00:30:55,440 --> 00:30:59,760 your Octa logs, your GCP logs, your Google Workspace logs and 530 00:30:59,760 --> 00:31:03,200 so your entralogs and so on. But it's not only logs, it's 531 00:31:03,200 --> 00:31:08,160 also the actual information on permission data that you get. 532 00:31:08,160 --> 00:31:11,520 So like permission data from GitHub or permission data from 533 00:31:12,520 --> 00:31:14,720 Salesforce or permission data from Monday. 534 00:31:15,120 --> 00:31:17,800 Those are actually very, very valid points. 535 00:31:18,000 --> 00:31:21,440 It's not just to see the the logs in terms of the usage. 536 00:31:21,720 --> 00:31:26,040 Even seeing kind of a permission was changed over time X amount 537 00:31:26,040 --> 00:31:30,920 of times or a permission was changed or elevated or de 538 00:31:30,920 --> 00:31:33,520 elevated. That's also a very good source 539 00:31:33,520 --> 00:31:36,720 of information. It's not just the fact that Jim 540 00:31:36,720 --> 00:31:39,640 now did the login or, or another login or another login. 541 00:31:40,480 --> 00:31:42,720 Yeah, yeah. That's important. 542 00:31:43,320 --> 00:31:48,120 So I think you explained why somebody would want to exit is 543 00:31:48,120 --> 00:31:50,560 what is the business problem that they're trying to solve. 544 00:31:50,760 --> 00:31:55,400 You talked about how the system works and identifying that it 545 00:31:55,400 --> 00:31:58,200 looks like Jeff's account is doing something that normally 546 00:31:58,200 --> 00:32:02,400 doesn't do. So I assume at that point you're 547 00:32:02,400 --> 00:32:06,280 doing some kind of alerting, like what is the output of the 548 00:32:06,280 --> 00:32:09,080 XMU system? Very, very good question. 549 00:32:09,080 --> 00:32:13,480 So I think what we realized that Exonius over the years is that 550 00:32:13,600 --> 00:32:16,760 visibility, observability is actually great. 551 00:32:16,960 --> 00:32:20,400 So observability, the way we define universal visibility is 552 00:32:20,400 --> 00:32:23,120 like not just doing the visibility layer, but also 553 00:32:23,120 --> 00:32:25,520 recommending of what it should look like. 554 00:32:25,640 --> 00:32:28,240 OK, so that's kind of observability, but you cannot 555 00:32:28,240 --> 00:32:31,200 really stop there. You need to drive then to action 556 00:32:31,840 --> 00:32:35,160 and this is something that they we've invested a lot over the 557 00:32:35,160 --> 00:32:39,000 last couple of years in Axonis in general in the platform of 558 00:32:39,000 --> 00:32:42,680 driving more actions and building our action repository 559 00:32:42,760 --> 00:32:46,240 sort of speak. So today we have over 400 560 00:32:46,320 --> 00:32:49,720 out-of-the-box actions that we can drive from the platform. 561 00:32:49,880 --> 00:32:53,760 Again, there are actions that are in the targeted systems that 562 00:32:53,760 --> 00:32:56,560 we connect to. So for example, an action can be 563 00:32:58,160 --> 00:33:03,200 decommissioning an account in Office 365 and an action can be 564 00:33:03,200 --> 00:33:09,480 a revoking and a token extension and action can be open an alert 565 00:33:09,480 --> 00:33:11,960 in your Splunk and so on and so on. 566 00:33:12,240 --> 00:33:16,160 So there is various kind of types I would say between just 567 00:33:16,160 --> 00:33:19,760 the e-mail alert and all the way to a kind of a more forceful 568 00:33:20,000 --> 00:33:22,880 enforcement that you can drive in an in an application. 569 00:33:23,480 --> 00:33:27,000 All of that are a set of actions that you can actually trigger 570 00:33:27,160 --> 00:33:31,840 with workflows in Axonis. So let's take an example, a very 571 00:33:31,840 --> 00:33:34,600 common one is non human accounts ownership. 572 00:33:34,680 --> 00:33:38,040 That's probably the most common use case that we come across 573 00:33:38,040 --> 00:33:40,240 with customers. They want to make sure that 574 00:33:40,240 --> 00:33:43,480 every non human account has an owner 100% of the times. 575 00:33:43,640 --> 00:33:47,920 So if Jeff now has five service accounts that he is responsible 576 00:33:47,920 --> 00:33:52,640 for tomorrow morning Jeff is moving to another section of the 577 00:33:52,640 --> 00:33:56,000 of the company and now no longer he's responsible for any service 578 00:33:56,000 --> 00:33:57,080 accounts. What do you do? 579 00:33:57,080 --> 00:34:00,760 You have those like headless service accounts that are 580 00:34:00,760 --> 00:34:03,920 spinning around. Nobody's is is taking ownership. 581 00:34:03,920 --> 00:34:06,520 You want to make sure that the immediately at that point of 582 00:34:06,520 --> 00:34:09,199 time there is an assigned ownership to somebody else. 583 00:34:09,280 --> 00:34:14,560 Let's say gym is the is the the the kind of super Uber admin in 584 00:34:14,560 --> 00:34:17,159 the company. And maybe by default, every time 585 00:34:17,320 --> 00:34:20,760 there is an admin that is moving that those service accounts 586 00:34:21,040 --> 00:34:24,159 immediately roll over to gym. You can have an easy workflow 587 00:34:24,159 --> 00:34:30,840 that that constantly monitors for anyone leaving, changing de 588 00:34:30,840 --> 00:34:34,719 assigned, etcetera from specific service account in AWS. 589 00:34:35,000 --> 00:34:38,719 And the moment it happens, this account is automatically 590 00:34:38,800 --> 00:34:42,239 assigned to GM. We drive the action in AWS that 591 00:34:42,239 --> 00:34:44,600 now the new admin of that service account is going to be 592 00:34:44,600 --> 00:34:47,199 GM. That's a very, very kind of easy 593 00:34:47,199 --> 00:34:49,719 example, but it can get more complicated than that. 594 00:34:49,719 --> 00:34:53,800 It can be kind of workflows that are around movers, for example. 595 00:34:53,800 --> 00:34:56,960 So people moving from one department to another, revoking 596 00:34:56,960 --> 00:34:59,920 all of their permissions by default or actually giving a 597 00:34:59,920 --> 00:35:03,520 grace time of not revoking the permissions and waiting and 598 00:35:03,520 --> 00:35:07,320 maybe raising a ticket or opening kind of an alert to the 599 00:35:07,400 --> 00:35:11,360 manager and so. On Mayor, I'm imagining that our 600 00:35:11,360 --> 00:35:15,440 listeners or people checking this out on YouTube, it's a lot 601 00:35:15,440 --> 00:35:19,600 to absorb because it seems like Axonia's really does. 602 00:35:19,760 --> 00:35:22,320 It's almost like a Smithsonian. Like you've got the 603 00:35:22,320 --> 00:35:25,320 intelligence, you get the visibility and the intelligence. 604 00:35:25,640 --> 00:35:31,240 You've got traditional IGA schools to manage your 605 00:35:31,240 --> 00:35:34,560 environment, but on top of that, you have this detective 606 00:35:34,840 --> 00:35:40,360 functionality to see when accounts have potentially been 607 00:35:40,360 --> 00:35:44,200 compromised and start to take action on that. 608 00:35:46,000 --> 00:35:50,480 How many how many years does it take for a client to roll out 609 00:35:50,480 --> 00:35:52,360 Axonius? Yeah. 610 00:35:52,360 --> 00:35:56,160 So, so actually use the very common we we hear the Swiss Army 611 00:35:56,160 --> 00:35:59,800 knife every time and and we didn't speak about it even when 612 00:35:59,800 --> 00:36:04,680 we prepared for the for this. So Swiss Army knife is something 613 00:36:04,680 --> 00:36:08,320 that we keep hearing again and again from customers because 614 00:36:08,480 --> 00:36:10,840 like you said, I think the breadth of functionality that 615 00:36:10,840 --> 00:36:14,520 exists index on his platform is really unbelievable. 616 00:36:15,400 --> 00:36:19,520 Now to some extent, we actually want to make sure that it's a 617 00:36:19,520 --> 00:36:23,320 very, let's say, easy to use Swiss Army knife, OK? 618 00:36:23,320 --> 00:36:26,600 So it would be very intuitive for a customer to know which 619 00:36:27,720 --> 00:36:33,280 like a wine screw bottle to open and which a specific knife to 620 00:36:33,280 --> 00:36:37,920 pull out of this Swiss knife and not not be puzzled by too much 621 00:36:37,920 --> 00:36:40,120 functionality and too much richness. 622 00:36:40,560 --> 00:36:45,640 And the way we do it is first, we're now applying AI within the 623 00:36:45,640 --> 00:36:49,080 platform, OK, of kind of recommending, so kind of more 624 00:36:49,080 --> 00:36:52,280 this agentic AI concept of asking a question and getting 625 00:36:52,280 --> 00:36:54,800 kind of the result and helping you navigate through. 626 00:36:55,440 --> 00:37:00,520 Plus also, we have a very, I would say, relatively intuitive 627 00:37:00,560 --> 00:37:06,600 and simplistic UI and UX ability that we applied especially in 628 00:37:06,600 --> 00:37:08,520 IGA. I think it's super important. 629 00:37:08,680 --> 00:37:13,480 And when we looked around to the existing IGA products out there, 630 00:37:13,480 --> 00:37:17,400 existing IGA tools out there, I must say, a lot of the UX that 631 00:37:17,400 --> 00:37:22,160 we found was very choppy, very kind of convoluted and and very 632 00:37:22,160 --> 00:37:24,520 not intuitive. And that's why we put ourselves 633 00:37:24,520 --> 00:37:28,640 as a, as kind of as a, a mission to make sure that it's very easy 634 00:37:28,640 --> 00:37:31,120 to use. So you can become an expert on 635 00:37:31,120 --> 00:37:36,360 Axonius, of course, endlessly. There's always more room to 636 00:37:36,360 --> 00:37:39,960 learn and more room to to do. And especially if you connect 637 00:37:39,960 --> 00:37:44,320 more data, then of course, each new data source has new aspects 638 00:37:44,320 --> 00:37:49,640 that it adds to the, it adds to the mix, you know, so as the 639 00:37:49,640 --> 00:37:53,320 more information that flows into XRM is, the richer it gets. 640 00:37:53,320 --> 00:37:56,800 So that's why you know you, it's almost endless how much you can 641 00:37:56,800 --> 00:38:00,080 become an expert. But I would say that with most 642 00:38:00,080 --> 00:38:03,440 of our customers, first we have our own kind of technical 643 00:38:04,000 --> 00:38:07,480 account managers that support customers during the onboarding 644 00:38:07,640 --> 00:38:09,080 and make sure that they are acquainted. 645 00:38:09,080 --> 00:38:12,320 We have also a lot of partners that they run very kind of 646 00:38:12,320 --> 00:38:16,440 rigorous training and the certification programs. 647 00:38:16,920 --> 00:38:20,520 But as a user, I believe within a matter usually of a of a 648 00:38:20,520 --> 00:38:24,400 month, a couple of months, you can easily kind of be a 649 00:38:24,400 --> 00:38:28,320 self-sufficient kind of expert sort of speak. 650 00:38:28,320 --> 00:38:30,880 And the moment you want to do something more complex or of 651 00:38:31,240 --> 00:38:34,240 course, we, we more than welcome the moment you see kind of a gap 652 00:38:34,240 --> 00:38:38,120 that we need to, to address, we, we actually welcome that input 653 00:38:38,120 --> 00:38:40,920 to work in there and achieve that with our customers. 654 00:38:41,560 --> 00:38:43,560 Right. So it seems like kind of getting 655 00:38:43,560 --> 00:38:48,400 off the block you can do relatively quickly. 656 00:38:49,000 --> 00:38:53,640 I'm wondering with your clients or your customers, how you know 657 00:38:53,640 --> 00:38:55,720 where do they normally start? So Jeff and I have been 658 00:38:55,720 --> 00:39:00,800 consultants for a long time. In this identity phase, we often 659 00:39:00,800 --> 00:39:03,360 use the term don't boil the ocean, right? 660 00:39:03,400 --> 00:39:05,760 Correct. You know, don't try to actually 661 00:39:05,840 --> 00:39:09,120 use the Swiss Army knife, but you don't need to learn how. 662 00:39:09,320 --> 00:39:11,600 Yeah, yeah, yeah. If you need to open a wine 663 00:39:11,600 --> 00:39:15,680 bottle, use the Corkscrew and leave the other things till you 664 00:39:15,680 --> 00:39:19,720 know phase two or whatever. Where do your clients? 665 00:39:19,800 --> 00:39:23,680 How do they usually start? So, so I think actually going 666 00:39:23,680 --> 00:39:28,520 back to this new category that Dartner created called IVIP, I 667 00:39:28,520 --> 00:39:31,320 think that's, that's actually a very, very good place to to 668 00:39:31,320 --> 00:39:34,360 start with Exonia. So creating this kind of 669 00:39:34,400 --> 00:39:39,880 visibility intelligence, making sure that you have the initial 670 00:39:40,360 --> 00:39:45,400 data sources connected. So kind of a maybe a dozen or 20 671 00:39:45,600 --> 00:39:48,920 initial data sources that are the most important ones for the 672 00:39:48,920 --> 00:39:53,360 organization connected, creating that first initial visibility, 673 00:39:53,360 --> 00:39:56,680 unified visibility within their compensation and start driving 674 00:39:56,680 --> 00:39:59,040 intelligence there. I would say that's probably 675 00:39:59,040 --> 00:40:03,360 where I would start most likely in the identity hygiene side of 676 00:40:03,360 --> 00:40:04,680 things. I think that's where you will 677 00:40:04,680 --> 00:40:08,640 start kind of driving very immediate value out of, you know 678 00:40:09,320 --> 00:40:12,320 off the shelf kind of within the first two months you will 679 00:40:12,320 --> 00:40:15,640 achieve identity hygiene that would have taken you years to 680 00:40:15,640 --> 00:40:17,920 achieve without something like a Sonius. 681 00:40:18,800 --> 00:40:22,640 And from there actually start kind of defining your own kind 682 00:40:22,640 --> 00:40:25,000 of road map into areas that are important for you. 683 00:40:25,000 --> 00:40:28,320 For example, you want to tackle non human accounts because 684 00:40:28,320 --> 00:40:32,560 that's kind of the new danger that they or the new risk that 685 00:40:32,560 --> 00:40:36,400 you associated in the company or you want to drive. 686 00:40:36,400 --> 00:40:39,640 As I mentioned before this Pam enhancement, we see that very 687 00:40:39,640 --> 00:40:42,360 common actually with with customers these days. 688 00:40:42,480 --> 00:40:45,600 So you can start there. You want to drive it more on 689 00:40:45,600 --> 00:40:48,560 kind of compliance perspective because you're you now need to 690 00:40:48,560 --> 00:40:52,880 have just the other day we had a prospect saying I need to meet 691 00:40:52,880 --> 00:40:59,120 my socks in December and I must have a basic IGA program running 692 00:40:59,120 --> 00:41:00,200 by December. Yeah. 693 00:41:00,280 --> 00:41:03,680 So that's kind of a good, a good compelling event to drive kind 694 00:41:03,680 --> 00:41:05,600 of compliance. Make sure you have your access 695 00:41:05,600 --> 00:41:07,960 reviews. That may be the first thing that 696 00:41:07,960 --> 00:41:10,840 you so it really differs from one area to another. 697 00:41:10,840 --> 00:41:12,760 And I think that's kind of the value of Axon use. 698 00:41:13,080 --> 00:41:17,120 That doesn't matter what's kind of the immediate use case that 699 00:41:17,120 --> 00:41:19,040 you want to achieve. The moment you get this 700 00:41:19,040 --> 00:41:22,240 visibility intelligence in place, you can then start 701 00:41:22,240 --> 00:41:26,440 navigating for your own need within your own organization as 702 00:41:26,440 --> 00:41:29,000 to what's the next step and the following step that you want 703 00:41:29,080 --> 00:41:31,840 that you want to take forward. How do your? 704 00:41:31,840 --> 00:41:35,720 Customers measure the value they get out of your solution. 705 00:41:37,080 --> 00:41:41,920 So one very easy area that they, we've heard from a lot of 706 00:41:41,920 --> 00:41:46,240 customers is by reducing the amount of cost that they need to 707 00:41:46,240 --> 00:41:50,520 have on their identity on, on their IAM program. 708 00:41:50,920 --> 00:41:54,680 So the amount of hours that they some, some are measuring, for 709 00:41:54,680 --> 00:41:57,760 example, by the amount of tickets that they that they need 710 00:41:57,760 --> 00:42:02,040 to manage the IAM tickets and that reduces significantly. 711 00:42:03,000 --> 00:42:06,920 Another one can be by the, the amount of time that it takes to 712 00:42:06,960 --> 00:42:11,400 to drive an audit A compliance. So our ability, for example, to 713 00:42:11,400 --> 00:42:15,680 drive very, very efficient access reviews, recommending 714 00:42:15,680 --> 00:42:19,760 actually managers what to what to approve, what to disapprove 715 00:42:19,760 --> 00:42:22,760 and so on. That actually makes it much more 716 00:42:22,760 --> 00:42:25,920 efficient and reduces the time for an audit. 717 00:42:26,640 --> 00:42:30,000 Another, another aspect of course is just by the fact that 718 00:42:30,440 --> 00:42:35,760 some companies need to have and IGA as as robust as, as can be 719 00:42:35,960 --> 00:42:39,680 IGA programming place and with Axonius they can achieve that in 720 00:42:39,680 --> 00:42:42,160 a matter of months. We, we just kind of had a 721 00:42:42,160 --> 00:42:47,080 customer out of out of Georgia, you mentioned Georgia before, so 722 00:42:47,880 --> 00:42:52,240 out of Georgia that they actually had to put an IGA 723 00:42:52,240 --> 00:42:54,520 program in place. They were managing their IGA 724 00:42:54,520 --> 00:42:58,440 manually for many years, like trying to do a lot of open 725 00:42:58,440 --> 00:43:01,640 source and scripts and so on. And they outgrown as a company. 726 00:43:01,640 --> 00:43:03,840 They already scaled up and they outgrown that. 727 00:43:04,640 --> 00:43:09,000 And their KPI was to get to an IGA program by the end of the 728 00:43:09,000 --> 00:43:13,440 year, make sure that they have a full identity, life cycle and so 729 00:43:13,440 --> 00:43:16,040 on. And I'm proud to say that with 730 00:43:16,040 --> 00:43:20,200 Exonucy, it didn't take a year. It took like 1/4 in order to in 731 00:43:20,200 --> 00:43:23,440 order to achieve that. So that that was a very kind of 732 00:43:23,600 --> 00:43:26,400 strong KPI they they were able to make to meet. 733 00:43:27,520 --> 00:43:29,840 So you're tapping one of the hardest parts of anything in 734 00:43:29,840 --> 00:43:31,720 identity, which is that visibility part, right? 735 00:43:32,040 --> 00:43:35,280 Collecting, correlating and saying OK, here's Jeff and all 736 00:43:35,280 --> 00:43:39,080 the X number of accounts, no pun intended, that I have, you know, 737 00:43:39,080 --> 00:43:42,320 across the environment. Where does it go from here? 738 00:43:42,320 --> 00:43:45,440 Because you mentioned things like IGA and I've always thought 739 00:43:45,440 --> 00:43:48,960 of IGA as sort of the center of the universe when it comes to I 740 00:43:48,960 --> 00:43:50,840 am right. It's the thing that typically 741 00:43:50,840 --> 00:43:54,080 would collect here is Jeff, and then here are all the systems 742 00:43:54,080 --> 00:43:55,880 that are connected to it off the different spokes. 743 00:43:56,520 --> 00:43:58,280 Where do you see Exonius going from here? 744 00:43:58,280 --> 00:44:02,480 Is it being that sort of source of truth for maybe not just 745 00:44:02,480 --> 00:44:04,960 identity but other assets and other things that your platform 746 00:44:04,960 --> 00:44:07,360 consumes as well or how do you see that taking place? 747 00:44:07,360 --> 00:44:09,040 Yes. Absolutely. 748 00:44:09,040 --> 00:44:12,080 So Axonius at the end of the day is a system of records. 749 00:44:12,080 --> 00:44:16,760 You know, we are a data company. What you can drive is a Nirvana 750 00:44:16,760 --> 00:44:20,560 of a data company is really to be a system of record and the 751 00:44:20,560 --> 00:44:22,640 source of truth for the organization. 752 00:44:22,920 --> 00:44:27,760 So we've already in many organizations are currently the 753 00:44:27,760 --> 00:44:32,400 source of truth in the kind of traditional asset world and they 754 00:44:32,400 --> 00:44:36,720 go to us as their source of truth for all of their physical 755 00:44:36,720 --> 00:44:40,440 assets, cloud assets and so on. In many organizations where the 756 00:44:40,440 --> 00:44:43,240 source of truth for anything to do with SAS in terms of 757 00:44:43,240 --> 00:44:46,800 configurations etcetera and absolutely also in identities. 758 00:44:46,800 --> 00:44:49,560 That's what we want to achieve. We want to be the source of 759 00:44:49,560 --> 00:44:52,800 truth, the system of records for for many others. 760 00:44:53,280 --> 00:44:57,800 One of our advisors when, when we were starting to think about 761 00:44:57,800 --> 00:45:02,480 identities, he was actually an advisor for us also on the SSPN 762 00:45:02,520 --> 00:45:06,120 side of things. And when we told him that, look, 763 00:45:06,120 --> 00:45:08,360 we, we are actually exploring identities, etcetera. 764 00:45:08,360 --> 00:45:10,720 And he said, are you really sure you want to do that? 765 00:45:10,880 --> 00:45:14,000 That's very, very hard to do. And we asked him why. 766 00:45:14,000 --> 00:45:16,240 Why do you think it's? He said, because you will become 767 00:45:16,240 --> 00:45:18,040 you. You need to take upon yourself 768 00:45:18,240 --> 00:45:21,480 to become the source of truth for identities. 769 00:45:21,560 --> 00:45:26,960 It's like that's a very kind of challenging task to take. 770 00:45:27,440 --> 00:45:30,280 And but then he continued in saying, but if there's any 771 00:45:30,280 --> 00:45:35,080 company I believe can do that, you already kind of prove that 772 00:45:35,080 --> 00:45:37,720 to me that you can do it in the, in the asset management set 773 00:45:37,720 --> 00:45:41,280 space and now in the SSPM space. So if there is a place you know 774 00:45:41,400 --> 00:45:44,240 that you should go to is that, but be prepared. 775 00:45:44,240 --> 00:45:48,080 It's going to be very, very hard and we like doing hard things. 776 00:45:48,080 --> 00:45:52,600 So so we we took the challenge. Well, you know, I ask that my 777 00:45:52,600 --> 00:45:54,880 question every all the time, like why am I an identity? 778 00:45:54,880 --> 00:45:57,160 And you're totally right, because it's always something 779 00:45:57,480 --> 00:45:59,560 that comes along. That source of truth is such an 780 00:45:59,560 --> 00:46:01,640 important part. But that's really only like half 781 00:46:01,640 --> 00:46:04,880 the equation in my mind. So that's great to collect all 782 00:46:04,880 --> 00:46:07,320 those data. A lot of companies collect data. 783 00:46:08,120 --> 00:46:10,720 The question after that is like, well, what do we do with it, 784 00:46:10,920 --> 00:46:12,280 right? Is there automation? 785 00:46:12,280 --> 00:46:13,600 Are there insights we can drive? Right? 786 00:46:13,640 --> 00:46:16,520 AI is kind of, you know, taking the forefront here of being that 787 00:46:16,520 --> 00:46:19,880 thing, but how do you look at automation of that data? 788 00:46:19,880 --> 00:46:21,360 Because it's one thing to discover. 789 00:46:21,360 --> 00:46:24,000 It's another thing to. Absolutely, absolutely. 790 00:46:24,000 --> 00:46:28,400 So as I mentioned before, visibility and observability is 791 00:46:28,400 --> 00:46:32,480 just kind of the first step driving action ability, that's 792 00:46:32,480 --> 00:46:35,840 kind of the end game. And the driving action ability 793 00:46:35,840 --> 00:46:38,880 in identities is, is probably the most important thing. 794 00:46:39,160 --> 00:46:42,600 You want to make sure that you have as much as automation as 795 00:46:42,600 --> 00:46:45,760 possible that you can rely on, of course, but as much 796 00:46:45,760 --> 00:46:48,760 automation as possible to drive your identity lifecycle 797 00:46:48,760 --> 00:46:52,400 management, as much automation as possible to drive your access 798 00:46:52,400 --> 00:46:55,600 reviews. For example, one of the ideas 799 00:46:55,600 --> 00:46:58,200 that that we heard from a customer is saying forget of all 800 00:46:58,200 --> 00:47:01,120 of those access you need, you need to have like self approve 801 00:47:01,920 --> 00:47:05,080 access reviews and you need to rely on employees in the company 802 00:47:05,080 --> 00:47:07,960 that will self approve their their own access. 803 00:47:08,440 --> 00:47:11,160 You then need maybe to have automation that will certify 804 00:47:11,360 --> 00:47:14,960 that their own self approval was actually the right one and there 805 00:47:14,960 --> 00:47:20,720 was no kind of segregation of duty, you know, bridges that 806 00:47:20,720 --> 00:47:22,440 happened. But if you can drive automation 807 00:47:22,440 --> 00:47:25,200 that constantly monitors that, that constantly check, you can 808 00:47:25,200 --> 00:47:30,040 actually save a lot of time. So the more automation that you 809 00:47:30,040 --> 00:47:32,440 drive, the better. And I think that at the end of 810 00:47:32,440 --> 00:47:36,280 the day, we also developed like a core workflow engine. 811 00:47:37,320 --> 00:47:42,160 The real key essence is by the amount of actions that that 812 00:47:42,160 --> 00:47:46,360 workflow engine can drive. And actions in our mind is the 813 00:47:46,360 --> 00:47:48,880 amount of actions you can drive in systems themselves. 814 00:47:48,880 --> 00:47:51,240 So we don't need to recreate actions. 815 00:47:51,440 --> 00:47:54,800 We believe today in every tool, in every product that exists in 816 00:47:54,800 --> 00:47:57,760 the organization, there is enough actions that can be taken 817 00:47:57,760 --> 00:47:59,520 there. We just need to be able to 818 00:47:59,520 --> 00:48:02,640 trigger them and and leverage them in the best manner. 819 00:48:03,240 --> 00:48:05,680 And there will be new actions that come up based on new data 820 00:48:05,680 --> 00:48:08,840 types and all that stuff, right? Absolutely, absolutely. 821 00:48:08,840 --> 00:48:12,800 And and again, I, I think going back to MLAI that that's kind of 822 00:48:12,800 --> 00:48:16,960 where where AI actually plays a very, very good role in terms of 823 00:48:17,160 --> 00:48:22,840 driving smart actions and simple actions that constantly pop up 824 00:48:22,840 --> 00:48:25,240 and, and, and can be addressed immediately. 825 00:48:25,240 --> 00:48:27,000 So. We're going to have more 826 00:48:27,000 --> 00:48:29,480 information, you know, in our show notes for people to check 827 00:48:29,480 --> 00:48:34,200 out exonius.com/IDAC. What can people expect when they 828 00:48:34,200 --> 00:48:36,240 get to that web page? Like what is, you know, 829 00:48:36,240 --> 00:48:38,160 something that if I'm listening to this, I'm like, all right, 830 00:48:38,160 --> 00:48:39,840 sounds interesting. Let me go check this out. 831 00:48:40,240 --> 00:48:42,320 Can you give us a little bit teaser of of what people will 832 00:48:42,320 --> 00:48:43,800 find there? Sure. 833 00:48:43,800 --> 00:48:46,640 You'll see there are a lot of use cases that we discussed here 834 00:48:47,400 --> 00:48:52,080 around, for example, NHI monitoring around our concept 835 00:48:52,080 --> 00:48:56,560 that we didn't go into here of moving from roles to rules. 836 00:48:56,600 --> 00:49:00,640 So the industry has ever been in kind of the role management 837 00:49:01,320 --> 00:49:05,480 chasing the tail type of exercise of constantly managing 838 00:49:05,480 --> 00:49:07,080 the roles. We believe that there should be 839 00:49:07,080 --> 00:49:09,360 a shift from roles to rule management. 840 00:49:09,360 --> 00:49:12,200 And you'll get to see some of our philosophy around there. 841 00:49:12,760 --> 00:49:15,440 You'll get to see some of the use cases such as Pam 842 00:49:15,440 --> 00:49:20,120 augmentation and so on, how we leverage a machine learning for 843 00:49:20,120 --> 00:49:23,960 role mining capabilities and many other kind of the use cases 844 00:49:23,960 --> 00:49:27,640 that that we discussed here. Are you guys going to be at any 845 00:49:27,640 --> 00:49:29,760 conferences coming up and when this airs, it'll be in 846 00:49:29,760 --> 00:49:32,880 September, but I imagine maybe things like Gartner or maybe 847 00:49:32,880 --> 00:49:35,760 Ideniverse or things like that. Yeah, absolutely. 848 00:49:35,760 --> 00:49:39,560 So we are, we are very much looking forward to being in 849 00:49:39,560 --> 00:49:43,160 Gartner Grapevine in the Identity and Access Management 850 00:49:43,160 --> 00:49:45,800 Summit. It's going to be our second one. 851 00:49:45,800 --> 00:49:48,960 So you know, we're we're newbies to the community. 852 00:49:49,720 --> 00:49:53,080 So it's a it's really, really and actually we didn't mention 853 00:49:53,080 --> 00:49:55,720 that at the beginning, but I think it's very humbling 854 00:49:55,720 --> 00:49:58,360 experience to be part of this identity community. 855 00:49:58,720 --> 00:50:03,680 I'm coming from cyberspace for many years to RSA and others and 856 00:50:03,760 --> 00:50:07,320 and cyber has become kind of a bit of a jungle to be honest. 857 00:50:08,080 --> 00:50:12,440 Whereas identity, the identity community still has this very 858 00:50:12,440 --> 00:50:15,400 unique tight community feel to it. 859 00:50:15,560 --> 00:50:18,480 I've seen it in, in Gartner Grapevine last year. 860 00:50:18,480 --> 00:50:20,880 I've seen it in Gartner in London last year. 861 00:50:20,880 --> 00:50:22,960 I've seen it in identity verse in Las Vegas. 862 00:50:23,240 --> 00:50:24,760 It's like people know each other. 863 00:50:24,920 --> 00:50:26,640 People really feel for each other. 864 00:50:26,640 --> 00:50:29,680 People have been in the trenches together and there's a lot of 865 00:50:29,680 --> 00:50:34,000 knowledge sharing and much less kind of, I would say competition 866 00:50:34,000 --> 00:50:37,280 or kind of much less kind of a wall building. 867 00:50:37,840 --> 00:50:42,160 So I, I really, really, I've enjoyed, you know, almost every 868 00:50:42,160 --> 00:50:43,960 practitioner I've I've met so far. 869 00:50:43,960 --> 00:50:47,320 So it's really, really nice to be part of this kind of cozy 870 00:50:48,120 --> 00:50:51,800 community, if I may say so. So yeah, definitely we're, we're 871 00:50:51,800 --> 00:50:54,440 going to be again in a, in Gartner in Grapevine. 872 00:50:54,480 --> 00:50:58,440 And I would welcome anyone that wants to have more time with us 873 00:50:58,440 --> 00:51:02,000 and we're gonna be their full team to kind of learn more about 874 00:51:02,000 --> 00:51:04,520 the product and what we've experienced and and also give us 875 00:51:04,520 --> 00:51:07,720 suggestions of what else we should be doing with this kind 876 00:51:07,720 --> 00:51:10,600 of data first approach. And of course, later of the 877 00:51:10,600 --> 00:51:13,920 year, you know, in in Gartner London and identity verse again. 878 00:51:13,960 --> 00:51:16,320 Absolutely. Well, Jim and I are going to be 879 00:51:16,320 --> 00:51:19,080 a Gartner, so we'll make it a point to stop by and say hello 880 00:51:19,080 --> 00:51:22,240 and give you the official fist bump of gratitude for the 881 00:51:22,240 --> 00:51:24,440 Identity Center podcast. I want to wrap up the 882 00:51:24,440 --> 00:51:27,720 conversation with a little bit sort of non I am kind of talk 883 00:51:27,720 --> 00:51:29,520 here. We were talking as we kind of 884 00:51:29,520 --> 00:51:33,440 got prepped for the session, that you got into skiing and you 885 00:51:33,440 --> 00:51:35,760 also have some kids. And I'm wondering, do your kids 886 00:51:35,760 --> 00:51:38,000 ski? First of all, that's the first 887 00:51:38,000 --> 00:51:39,360 question. Do your kids ski yet? 888 00:51:40,280 --> 00:51:42,400 Yes, so both of my daughters ski. 889 00:51:43,360 --> 00:51:46,600 I have a four year old daughter and a 7 1/2 year old daughter. 890 00:51:47,240 --> 00:51:49,560 The four year old daughter started skiing last year. 891 00:51:49,560 --> 00:51:53,120 So for somebody from Israel, that's not, not normal. 892 00:51:53,120 --> 00:51:54,560 We don't have a lot of snow in Israel. 893 00:51:55,360 --> 00:51:59,320 So, but yeah, I, I made it as a kind of, as a, as a mission to 894 00:51:59,520 --> 00:52:03,160 make sure that my, my passion and hobby I can enjoy with my 895 00:52:03,160 --> 00:52:06,160 daughters. I like enjoying stuff with them 896 00:52:06,160 --> 00:52:07,880 and, and having the experience with them. 897 00:52:08,080 --> 00:52:11,480 Speaking about identity, I like kind of see how their identity 898 00:52:11,480 --> 00:52:13,920 is being built, you know, over the years. 899 00:52:14,160 --> 00:52:17,000 And for me, skiing is part of my identity. 900 00:52:17,000 --> 00:52:20,480 And I, I'm still waiting for the, you know, for the time 901 00:52:20,480 --> 00:52:22,720 where I can be on the slopes together just with the two of 902 00:52:22,720 --> 00:52:25,400 them. And, but it's, it's great to see 903 00:52:25,400 --> 00:52:28,320 how they, they first, they love the snow, which was like the 904 00:52:28,320 --> 00:52:30,480 first fear. I didn't know how they will they 905 00:52:30,480 --> 00:52:33,680 will take. And secondly, they actually kind 906 00:52:33,680 --> 00:52:36,760 of enjoyed the challenge of learning something new that is 907 00:52:36,760 --> 00:52:39,520 not very common. And it's like they're they're a 908 00:52:39,520 --> 00:52:41,960 thing. So that's that's a very, very 909 00:52:41,960 --> 00:52:45,240 nice thing to see. So I've never been skiing and I 910 00:52:45,240 --> 00:52:48,480 feel like I would probably be on the four year old's level of 911 00:52:49,000 --> 00:52:51,880 teach me how to ski. Like what is what is a pro tip 912 00:52:51,880 --> 00:52:54,280 for people out there that are either like me, never been 913 00:52:54,280 --> 00:52:56,800 skiing before or have, you know, younger children? 914 00:52:57,360 --> 00:52:59,760 What is, was there like a tip or something that you can give 915 00:52:59,760 --> 00:53:01,880 people say hey, here's how I would start. 916 00:53:02,000 --> 00:53:05,920 I think the first thing is like forget about, like most people 917 00:53:05,920 --> 00:53:09,600 fear about kind of the moment you're on the skis and you don't 918 00:53:09,600 --> 00:53:12,480 have the regular control that you have over your feet, you 919 00:53:12,480 --> 00:53:16,720 need to just go with the flow. OK, So don't be afraid to fall. 920 00:53:16,760 --> 00:53:19,280 Actually falling is great. The earlier you fall, the better 921 00:53:19,760 --> 00:53:21,280 because then you know what it is. 922 00:53:21,280 --> 00:53:25,080 So like I encourage my daughters to fall actually, because the 923 00:53:25,080 --> 00:53:26,880 month they fall and they know how to get up. 924 00:53:27,120 --> 00:53:29,600 That's, that's good. You know, it's, it's kind of 925 00:53:29,600 --> 00:53:32,720 like in, in, you know, in innovation, you need to fail 926 00:53:32,720 --> 00:53:35,240 fast. So I would, I would say that 927 00:53:35,240 --> 00:53:37,160 that's probably the best advice to fail fast. 928 00:53:37,160 --> 00:53:41,120 So to fall early and kind of that removes the the fear away 929 00:53:41,360 --> 00:53:44,240 and then just go with the flow like your legs will will let you 930 00:53:44,560 --> 00:53:46,320 will will take you on, Don't worry. 931 00:53:47,280 --> 00:53:51,320 Is there a dream skiing trip that you'd like to take with 932 00:53:51,320 --> 00:53:53,480 your kids? Oh, absolutely. 933 00:53:53,480 --> 00:53:56,720 Yeah. So the place I I enjoyed most 934 00:53:56,720 --> 00:54:00,040 skiing in, which is like phenomenal, I advise any ski 935 00:54:00,320 --> 00:54:03,240 lover to go, is in Hokkaido in Japan. 936 00:54:04,880 --> 00:54:09,560 You ski on a volcano. You have powder snow almost all 937 00:54:09,560 --> 00:54:13,880 year round, like all season round, beautiful views. 938 00:54:14,040 --> 00:54:17,280 You know, it's not as high, but beautiful, beautiful views. 939 00:54:17,600 --> 00:54:20,360 Then at the end of the day, you end in an on sand, which is a 940 00:54:20,360 --> 00:54:23,680 hot spring, which is another experience. 941 00:54:23,680 --> 00:54:27,200 And I love Japanese food. So you have best Japanese food 942 00:54:27,200 --> 00:54:30,400 that you can dream of. So yeah, my, my dream is really 943 00:54:30,400 --> 00:54:33,920 taking my daughter. And I actually we went with our 944 00:54:33,920 --> 00:54:36,720 daughters to Japan last year and they love Japan. 945 00:54:37,680 --> 00:54:40,880 My my young girl the other day was at camp and she did the 946 00:54:40,880 --> 00:54:44,000 cupcake and that she came back and said, see that? 947 00:54:44,080 --> 00:54:45,680 You see what, What did I draw here? 948 00:54:45,840 --> 00:54:47,800 I told her it's a mountain. She said, no, it's not the 949 00:54:47,800 --> 00:54:50,880 mountain, it's Mount Fuji. I want to be back there. 950 00:54:52,000 --> 00:54:55,160 So yeah, they love Japan. So definitely going skiing in 951 00:54:55,160 --> 00:54:57,600 Japan, in Hokkaido with my daughters, that's that. 952 00:54:57,600 --> 00:55:00,240 That will be a dream come true. That sounds great. 953 00:55:00,240 --> 00:55:02,680 I mean, obviously it made an impression if they're drawing 954 00:55:02,680 --> 00:55:04,400 mountain, you know, drawing pictures of mountains of that 955 00:55:04,400 --> 00:55:06,400 I've. Only been to Japanese airports. 956 00:55:06,880 --> 00:55:10,520 They keep talking about Japan every almost every other day. 957 00:55:10,840 --> 00:55:12,680 That's a bucket list spot for me, Jim. 958 00:55:13,240 --> 00:55:14,960 Have you been skiing? Jim, I think I might have asked 959 00:55:14,960 --> 00:55:17,320 you this before. Yeah, yeah, I've skied a few 960 00:55:17,320 --> 00:55:21,920 times, but I can I consider myself a beginner or someone who 961 00:55:21,960 --> 00:55:25,120 sucks at it. So at this I can really give you 962 00:55:25,120 --> 00:55:27,000 tips. First off, I think I'm yours, 963 00:55:27,000 --> 00:55:28,200 right? You're going to fall. 964 00:55:29,160 --> 00:55:33,800 Just wear a lot of padding. I don't try to go skiing in like 965 00:55:33,800 --> 00:55:38,560 blue jeans and like you got to get ski pants because otherwise 966 00:55:38,560 --> 00:55:43,560 you end up wet and cold and then it's just like a bad experience. 967 00:55:43,560 --> 00:55:48,000 So if you're going to do it, I say get, you know, make the 968 00:55:48,000 --> 00:55:51,640 investment, get good ski pants, a good ski jacket so you're not 969 00:55:51,640 --> 00:55:56,240 cold the whole time. And then so my #1 tip would be 970 00:55:56,240 --> 00:56:00,680 take a lesson. Even if you're in your 50s or 971 00:56:01,000 --> 00:56:05,160 even older, it might be kind of embarrassing to be there with 972 00:56:05,160 --> 00:56:12,720 Amir's 4 year old but or she even she might fly by you as you 973 00:56:12,720 --> 00:56:15,480 are taking your lesson. Who cares? 974 00:56:15,480 --> 00:56:19,240 Just suck up your ego and do the lesson. 975 00:56:19,440 --> 00:56:21,360 Not at all. That, that that's exactly what 976 00:56:21,360 --> 00:56:24,480 my, my wife did a few years ago. So when we got married, I told 977 00:56:24,480 --> 00:56:27,320 her, too bad you have to learn skiing. 978 00:56:27,640 --> 00:56:29,440 That's what we're going to do every winter. 979 00:56:29,680 --> 00:56:32,400 And actually, yeah, she she took a lesson and, you know, she was 980 00:56:32,400 --> 00:56:34,480 already old. She took a lesson. 981 00:56:34,480 --> 00:56:37,800 And actually, she started at the beginning she was cursing me. 982 00:56:38,040 --> 00:56:40,760 But now, now she's starting to get the hang of it. 983 00:56:40,760 --> 00:56:42,000 And she she loves it. Yeah. 984 00:56:42,800 --> 00:56:45,280 Yeah, you're going to have to edit that out because Amir just 985 00:56:45,280 --> 00:56:48,760 called his wife old on and it's good. 986 00:56:48,760 --> 00:56:53,320 This episode is going to live on the Internet forever and I don't 987 00:56:53,320 --> 00:56:54,880 want the poor guy to get in trouble. 988 00:56:54,880 --> 00:56:56,440 So you're absolutely. Right. 989 00:56:57,240 --> 00:56:59,880 Maybe we'll use AI to like, you know, over dub it with like, you 990 00:56:59,880 --> 00:57:03,760 know, experienced or something like that, right yeah wise, 991 00:57:03,800 --> 00:57:04,920 right. Something that's like that. 992 00:57:05,560 --> 00:57:07,640 Those are good tips. And the other thing I like I 993 00:57:07,640 --> 00:57:10,280 think I like about skiing is you can be totally anonymous if you 994 00:57:10,280 --> 00:57:12,680 want to do it right. So if you are sort of and you 995 00:57:12,680 --> 00:57:16,160 know that self-conscious, you can throw on a ski goggles and a 996 00:57:16,280 --> 00:57:19,680 pad and you'll go to, you know, I would put on like the old 997 00:57:19,680 --> 00:57:22,600 Groucho Marx glasses with the fake mustache, the big nose, 998 00:57:22,600 --> 00:57:24,760 just to be, you know, clear, you know, that kind of thing. 999 00:57:25,720 --> 00:57:28,960 And and but so Jim, you mentioned the wearing the ski 1000 00:57:28,960 --> 00:57:33,560 pants as a Chicagoan and that for my almost my entire life, 1001 00:57:34,200 --> 00:57:37,840 you know, I'm thinking like shorts and like, you know, you 1002 00:57:37,840 --> 00:57:39,600 know, a hoodie, right, something like that. 1003 00:57:39,600 --> 00:57:42,800 Like that's the official winter gear of a of a true Chicagoan, I 1004 00:57:42,800 --> 00:57:45,440 feel like. Yeah, but a true Chicago is not 1005 00:57:45,440 --> 00:57:50,400 falling in in the snow every 5 minutes, so you do what you 1006 00:57:50,400 --> 00:57:53,960 want. All right, let's go ahead and 1007 00:57:53,960 --> 00:57:56,400 leave it there for this week. Amira, thank you so much for 1008 00:57:56,400 --> 00:57:58,400 spending time with us and getting us up to speed on 1009 00:57:58,400 --> 00:57:59,480 Exponia. So we're going to have a bunch 1010 00:57:59,480 --> 00:58:01,360 of links in our show notes for people to check out. 1011 00:58:01,760 --> 00:58:03,840 We'll have a link to your LinkedIn profile so people can 1012 00:58:03,840 --> 00:58:06,760 reach out with either questions about that or skiing or whatever 1013 00:58:06,760 --> 00:58:09,040 it may be. You can visit them on the web, 1014 00:58:09,040 --> 00:58:11,520 axonious.com/idac. There'll be some more 1015 00:58:11,520 --> 00:58:13,200 information right there. Again, that'll be a link in our 1016 00:58:13,200 --> 00:58:16,320 show notes. And yeah, I think that'll do it 1017 00:58:16,320 --> 00:58:17,560 for us. Visit us on the web 1018 00:58:17,640 --> 00:58:20,440 idacpodcast.com. Show support. 1019 00:58:20,440 --> 00:58:22,920 Like subscribe, do all those fun things to share out with people 1020 00:58:22,920 --> 00:58:25,520 so we can get great guests like a mirror to come back and share 1021 00:58:25,520 --> 00:58:28,040 more stories with us. So with that, we'll leave it for 1022 00:58:28,040 --> 00:58:30,480 this week. Thanks everyone for watching and 1023 00:58:30,480 --> 00:58:32,920 or listening and we'll talk with you all in the next one. 1024 00:58:35,280 --> 00:58:38,360 You've been listening to Identity at the Center. 1025 00:58:38,680 --> 00:58:42,800 We hope you've enjoyed the show. Make sure to like, rate and 1026 00:58:42,800 --> 00:58:46,400 review, and we'll be back soon. But in the meantime, hit the 1027 00:58:46,400 --> 00:58:49,840 website at identity@thecenter.com. 1028 00:58:50,440 --> 00:58:54,520 See you next time on Identity at the Center.