1 00:00:02,520 --> 00:00:06,519 Speaker 1: Bloomberg Audio Studios, podcasts, radio. 2 00:00:06,720 --> 00:00:09,520 Speaker 2: News, Nikesh, I think we get right into the numbers, right. 3 00:00:09,640 --> 00:00:14,040 Speaker 2: The situation is for your EPs guidance come down, revenue 4 00:00:14,080 --> 00:00:16,159 Speaker 2: is beaten, and so I'm trying to understand, like the 5 00:00:16,280 --> 00:00:19,000 Speaker 2: environment that you're in, you know, what is it that 6 00:00:19,000 --> 00:00:22,000 Speaker 2: that's weighing on profitability for the balance of this year. 7 00:00:23,320 --> 00:00:24,720 Speaker 3: Well, first of all, nice to see you, Ed, and 8 00:00:24,760 --> 00:00:27,000 Speaker 3: thank you for having me on. I think the market 9 00:00:27,080 --> 00:00:29,960 Speaker 3: is not paying attention to our numbers carefully. We just 10 00:00:30,040 --> 00:00:32,000 Speaker 3: completed our largest acquisition. 11 00:00:31,560 --> 00:00:33,880 Speaker 4: In cyber Arc. We had a great quarter. 12 00:00:34,080 --> 00:00:38,440 Speaker 3: Our numbers are across every known consensus metric. The market 13 00:00:38,479 --> 00:00:40,680 Speaker 3: is not understanding that our guidance for the next two 14 00:00:40,720 --> 00:00:43,920 Speaker 3: quarters includes cyber Arc. If you take the consensus cyber 15 00:00:44,040 --> 00:00:47,400 Speaker 3: Arc and ours, we are actually getting above the collective consensus. 16 00:00:47,479 --> 00:00:49,920 Speaker 3: But the market hasn't understood the dilution of shares, so 17 00:00:49,960 --> 00:00:57,560 Speaker 3: I think they have it wrongs. Actually, the board I always. 18 00:00:57,520 --> 00:00:59,040 Speaker 4: Above consens across the board. 19 00:00:59,240 --> 00:01:01,760 Speaker 3: These are the post market bots which haven't figured this out. 20 00:01:02,480 --> 00:01:04,800 Speaker 2: I always enjoy you joining us on the network. You're 21 00:01:04,840 --> 00:01:08,199 Speaker 2: always honest, You're always very specific about M and A. Right, 22 00:01:09,200 --> 00:01:11,280 Speaker 2: the math that people are doing is the guide for 23 00:01:11,319 --> 00:01:14,320 Speaker 2: next gen ARR growth is fifty three to fifty four 24 00:01:14,319 --> 00:01:18,440 Speaker 2: percent cyber arc chronosphere, but that would suggest that that 25 00:01:18,720 --> 00:01:22,360 Speaker 2: organically growth is neared a sort of twenty percent. Can 26 00:01:22,400 --> 00:01:24,280 Speaker 2: you see the math that they're doing. 27 00:01:24,760 --> 00:01:26,360 Speaker 3: Yes, I see the map, but I think if they 28 00:01:26,440 --> 00:01:31,560 Speaker 3: listen carefully, cyber Arc computes ARR differently from us, So 29 00:01:31,600 --> 00:01:34,120 Speaker 3: we've had to trip out a few hundred million dollars 30 00:01:34,160 --> 00:01:36,760 Speaker 3: of cyber RKERR. Hence, if you dig that out and 31 00:01:36,800 --> 00:01:39,920 Speaker 3: netted back, we're actually doing better collectively than we're guided. 32 00:01:39,959 --> 00:01:42,880 Speaker 3: This all clarify by tomorrow morning as the market opens, 33 00:01:42,880 --> 00:01:45,920 Speaker 3: but I think the market hasn't understood the comments are 34 00:01:45,920 --> 00:01:49,520 Speaker 3: CFO made around the fact that our computation of ARR 35 00:01:50,080 --> 00:01:50,680 Speaker 3: is different. 36 00:01:50,800 --> 00:01:53,760 Speaker 4: It's more conservative than cyber Arc. Cyber arcs is more 37 00:01:54,000 --> 00:01:55,240 Speaker 4: as aggressive than ours. 38 00:01:55,480 --> 00:01:58,360 Speaker 1: If you turn down their ARR down to the way 39 00:01:58,440 --> 00:02:01,640 Speaker 1: we compute it, actually actively, our RIRR guidance is a 40 00:02:01,760 --> 00:02:05,680 Speaker 1: success of what we previously guide it organically individually. 41 00:02:07,320 --> 00:02:11,960 Speaker 2: On the call, you mentioned a nine figure chronosphed deal. 42 00:02:12,639 --> 00:02:16,120 Speaker 2: You didn't name the customer. Somebody from the cell side 43 00:02:16,120 --> 00:02:18,400 Speaker 2: asked you about the deal, they didn't ask you to 44 00:02:18,480 --> 00:02:19,320 Speaker 2: name the customer. 45 00:02:19,600 --> 00:02:23,160 Speaker 4: Who's the customer in a cat it's a popular LLLM 46 00:02:23,200 --> 00:02:23,480 Speaker 4: out there. 47 00:02:23,520 --> 00:02:25,720 Speaker 3: I think more importantly, what is there to understand is 48 00:02:25,720 --> 00:02:28,600 Speaker 3: that Cronis Fair is a net new startup. They came 49 00:02:28,680 --> 00:02:31,000 Speaker 3: up with a new way of doing observability which is 50 00:02:31,040 --> 00:02:34,480 Speaker 3: much more cost effective, much more efficient, and can scale 51 00:02:34,520 --> 00:02:37,000 Speaker 3: to the volume that elms are putting out there. That's 52 00:02:37,040 --> 00:02:39,040 Speaker 3: the reason we bought the company, the fact that two 53 00:02:39,080 --> 00:02:41,680 Speaker 3: hundred and fifty engineers can build something so amazing that 54 00:02:41,840 --> 00:02:46,600 Speaker 3: provides a leap frog opportunity against current players in observability. 55 00:02:47,000 --> 00:02:50,079 Speaker 3: That's what we bought them for. They've been under tests 56 00:02:50,160 --> 00:02:53,600 Speaker 3: for many months with this LLM. They've fully been accepted 57 00:02:53,600 --> 00:02:56,519 Speaker 3: across the platform. They will be replacing an incumbent vendor, 58 00:02:56,960 --> 00:02:59,560 Speaker 3: and as that continues to grow, we expect to see 59 00:02:59,560 --> 00:03:02,600 Speaker 3: continued growth of RR for that one customer. But additionally, 60 00:03:02,800 --> 00:03:04,720 Speaker 3: obviously knos Fair is talking to a whole bunch of 61 00:03:04,720 --> 00:03:07,919 Speaker 3: net new customers who are looking for either get off there, 62 00:03:08,120 --> 00:03:12,840 Speaker 3: do it yourself observability platforms or the place expensive observable 63 00:03:12,919 --> 00:03:14,919 Speaker 3: platforms that they've subscribed to in the past. 64 00:03:15,800 --> 00:03:19,400 Speaker 2: Nikesh like observability is so core to what is happening 65 00:03:19,480 --> 00:03:23,200 Speaker 2: Inegentic right now, if we move on the assumption that 66 00:03:23,280 --> 00:03:27,080 Speaker 2: the customer is one of the key frontier labs, would 67 00:03:27,120 --> 00:03:28,880 Speaker 2: you just talk a little bit about why they came 68 00:03:28,919 --> 00:03:32,600 Speaker 2: to you for security rather than do security themselves. 69 00:03:32,600 --> 00:03:32,639 Speaker 3: That. 70 00:03:33,160 --> 00:03:36,160 Speaker 2: I know that might sound like silly question, but actually 71 00:03:36,640 --> 00:03:38,760 Speaker 2: you know a lot of the frontier labs have teams 72 00:03:38,840 --> 00:03:42,200 Speaker 2: right they're looking at this issue themselves. They see value 73 00:03:42,240 --> 00:03:44,520 Speaker 2: clearly in what parallelto networks is offering. 74 00:03:45,600 --> 00:03:48,960 Speaker 4: Well, the number observability is beyond the model. Right. 75 00:03:49,000 --> 00:03:51,520 Speaker 3: The model LM people are focused on making sure their 76 00:03:51,520 --> 00:03:52,680 Speaker 3: model is amazing. 77 00:03:52,360 --> 00:03:54,000 Speaker 4: It does all the things that are expected to do. 78 00:03:54,040 --> 00:03:55,800 Speaker 3: But observability is to look at it from an end 79 00:03:55,800 --> 00:03:58,520 Speaker 3: to end perspective to see how do they make sure 80 00:03:58,560 --> 00:04:01,280 Speaker 3: that the customers are theirs who are using these things 81 00:04:01,480 --> 00:04:04,600 Speaker 3: and the usage continues to double almost every quarter. How 82 00:04:04,600 --> 00:04:06,640 Speaker 3: do they make sure that all their systems, our low 83 00:04:06,720 --> 00:04:10,160 Speaker 3: latency are working perfectly and there's nothing in the entire 84 00:04:10,280 --> 00:04:12,600 Speaker 3: end to end delivery chain that is underperforming. 85 00:04:12,640 --> 00:04:14,040 Speaker 4: So that's what observability does. 86 00:04:14,200 --> 00:04:16,400 Speaker 3: The reason they're coming to us is because they're busy 87 00:04:16,440 --> 00:04:19,279 Speaker 3: building the best models, applying their AI research to the models. 88 00:04:19,480 --> 00:04:22,039 Speaker 3: We're busy with Thronosphair making sure that the end to 89 00:04:22,120 --> 00:04:25,080 Speaker 3: end proposition works and there is very low latency. 90 00:04:25,080 --> 00:04:26,000 Speaker 4: By the way, this app. 91 00:04:26,080 --> 00:04:28,720 Speaker 3: This is true for not just LLLM, this is true 92 00:04:28,760 --> 00:04:31,240 Speaker 3: for every consumer app there is out there ability to 93 00:04:31,279 --> 00:04:34,440 Speaker 3: take Uber, door, Dash or YouTube. Every one of these 94 00:04:34,760 --> 00:04:38,279 Speaker 3: has to have an underpinning observability platform to make sure 95 00:04:38,320 --> 00:04:40,960 Speaker 3: that it's fully available ninety nine point nine nine percent 96 00:04:41,000 --> 00:04:44,200 Speaker 3: of the time, so that because every minute it is 97 00:04:44,240 --> 00:04:47,640 Speaker 3: not working at the capability and the latency that is 98 00:04:47,640 --> 00:04:49,279 Speaker 3: required is lost revenue. 99 00:04:50,200 --> 00:04:53,359 Speaker 2: Nickish very quickly your acquired KOI. The idea is greater 100 00:04:53,520 --> 00:04:57,640 Speaker 2: visibility into AI threats. But just succinctly, what problem did 101 00:04:57,640 --> 00:04:59,520 Speaker 2: that solve for you on the team? What are you getting? 102 00:05:00,320 --> 00:05:02,320 Speaker 3: Yeah, look, I think if you look at the adoption 103 00:05:02,440 --> 00:05:05,480 Speaker 3: of AI and at the enterprise end, you were seeing 104 00:05:05,560 --> 00:05:08,200 Speaker 3: a tremendous amount of adoption in vibecoding. People are using 105 00:05:08,240 --> 00:05:12,960 Speaker 3: cloud code, Cursor, Codex, and many many open source coding platforms. 106 00:05:13,000 --> 00:05:15,520 Speaker 3: As they use it, all that action is happening at 107 00:05:15,520 --> 00:05:19,000 Speaker 3: the endpoint, at the developer laptop, and that's where that's 108 00:05:19,040 --> 00:05:22,680 Speaker 3: an uncovered area of security. You have to protect that laptop, 109 00:05:22,760 --> 00:05:25,600 Speaker 3: that endpoint or the developer to ensure that you can 110 00:05:25,640 --> 00:05:27,600 Speaker 3: deliver code safely and security. 111 00:05:27,960 --> 00:05:30,040 Speaker 4: Coy saw the opportunity inn here and a half ago. 112 00:05:30,400 --> 00:05:34,040 Speaker 3: They build a capability, they have hot people are adopting 113 00:05:34,040 --> 00:05:36,880 Speaker 3: them across the board. Anyone who's trying to use vibecoding, 114 00:05:36,920 --> 00:05:39,320 Speaker 3: anybody's trying to use get on this recording bandwagon. 115 00:05:39,400 --> 00:05:42,719 Speaker 4: Find efficiencies, need that security at the end point. This 116 00:05:42,839 --> 00:05:45,359 Speaker 4: is different than other endpoint security. Both US and. 117 00:05:45,279 --> 00:05:48,520 Speaker 3: Another place in the industry sell called ADR. This is 118 00:05:48,640 --> 00:05:51,360 Speaker 3: very specific to endpoint security for agentic capability. 119 00:05:51,480 --> 00:05:54,440 Speaker 4: That's what COY does. So that's the reason we acquired COY. 120 00:05:55,400 --> 00:05:58,599 Speaker 2: A Keshra pala alto Network CEO, jumping straight from the 121 00:05:58,600 --> 00:06:00,560 Speaker 2: earning school to bringing back television