Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: You're listening to Bloomberg Business Week with Carol Masser and
Speaker 2: Tim Stenovek on Bloomberg Radio.
Speaker 3: Shares of the more than thirty nine billion dollar cloud
Speaker 3: security and software companies z Scaler are easily outperforming both
Speaker 3: the S and P five hundred and Nasdaq one hundred today.
Speaker 3: The stock is up nearly forty percent year to date,
Speaker 3: and yet we did see shares under pressure today, dropping
Speaker 3: nearly four percent after Bernstein downgraded the software company to
Speaker 3: market perform from outperform on growth concerns. Bernstein, by the way,
Speaker 3: setting its price target on the stock to two sixty
Speaker 3: for a share. That's a five percent increase from the
Speaker 3: Friday close. I should put out that initially Bernstein when
Speaker 3: the company reported earnings last week, they initially maintained their
Speaker 3: outperform rating. So there's been a lot of movement allis
Speaker 3: in general, tim a flurry of them weighing in, some
Speaker 3: raising their price targets on the stock, others lowering them.
Speaker 3: And we should point out the stock did drop about
Speaker 3: thirteen percent last week. That was on Wednesday following their earnings.
Speaker 1: Yeah, the forecast was annual revenue that was only slightly
Speaker 1: above estimates from one of the company were joined by
Speaker 1: Jay Chawdry, founder, chairman and CEO of z Scaler. He
Speaker 1: joins us from San Diego, also San Jose. Excuse me
Speaker 1: also with us as somebody who knows this company very well,
Speaker 1: Bloomberg Intelligence's global head of Tech research, Man Deep saying,
Speaker 1: he joins us here in the studio, Jay, I just
Speaker 1: want to start with you the growth concerns, the disappointment
Speaker 1: over the annual revenue forecast that was only slightly above estimates.
Speaker 2: Is growth slowing, not at all. We had an outstanding quarter.
Speaker 2: Our AIRR growth twenty six percent, revenue growth twenty six percent,
Speaker 2: free cash flow margin fifty two percent, operating margin twenty
Speaker 2: two percent. We beat all the metrics that Wall Street
Speaker 2: was looking for. In fact, if you take our free
Speaker 2: cash flow margin and add it to our revenue growth,
Speaker 2: that's seventy eight percent. That beats the rule of forty
Speaker 2: that many investors look for very very well. And this
Speaker 2: is at scale of three billion dollars or higher. There
Speaker 2: are only about five pure play enterprise SaaS companies that
Speaker 2: are in that unique class, So you're done extremely well.
Speaker 2: We are very proud of what we delivered and be
Speaker 2: passed a meaningful beat. We did and raised our annual target,
Speaker 2: So I think we're very pleased with it. I think
Speaker 2: investors get it wrong from time to time. This is
Speaker 2: one of those times.
Speaker 3: That's what's going to ask you know what, do you
Speaker 3: think investors just got it wrong? Because I mean, thirteen
Speaker 3: percent is a pretty big hit, So you think, I mean,
Speaker 3: that's not like them wavering at all. They really wanted
Speaker 3: more from you guys. I mean the expectations were certainly high.
Speaker 2: Look, markets do what they do. I have one focus,
Speaker 2: keep on innovating and serving our customers. And those innovations
Speaker 2: started with zero trust architecture with a chained the world
Speaker 2: of old school firewalls and VPNs. And now as AI
Speaker 2: security is coming, a security is becoming a big concern
Speaker 2: and zero trust that we pioneered is the foundation of it.
Speaker 2: So we have amazing interest from our customers. That's why
Speaker 2: we're able to deliver these strong numbers. Over forty five
Speaker 2: percent Fortune five hundred companies trust us, depend upon us,
Speaker 2: so I'm very bolish about our future.
Speaker 4: So talking about AI security, I mean, you have a
Speaker 4: business model that's reliant on companies hiring more people and
Speaker 4: you have a C based model, how does that change
Speaker 4: with AI security? Because AI, you know what we are
Speaker 4: seeing out there is more consumption based. So how does
Speaker 4: that impact you and your business?
Speaker 2: It's a good question. So we started out with bringing
Speaker 2: zero trust for users, so users can access applications without
Speaker 2: being on the company network, and natural pricing for that
Speaker 2: is user based. Then we move the model to our architecture.
Speaker 2: The next thing, how about zero trust communication for workloads
Speaker 2: cloud workloads that's actually based on number of workloads and
Speaker 2: actually mount traffic, so it's not just user based. If
Speaker 2: you think about AI security, there are many facets of
Speaker 2: a security well. One of the biggest thing our customers
Speaker 2: look for is as every company starts using a lot
Speaker 2: of agents. These agents are some like people. They need
Speaker 2: to access their applications, they need to talk to other agents.
Speaker 2: So we are extending our zero trust exchange that are
Speaker 2: designed for users and workloads and branches now to agentic
Speaker 2: exchange so that right agent can talk to right agent
Speaker 2: and right application. So obviously there's an opportunity for us
Speaker 2: to secure that communication. Yes, the number of users may
Speaker 2: not grow significantly, but I believe every company will have
Speaker 2: scores of agents for every single employee and they need
Speaker 2: to be secured and we are extremely well positioned to
Speaker 2: handle that.
Speaker 4: And talking about agents, it sounds like one of your
Speaker 4: biggest competitors is doubling down on observability and identity, especially
Speaker 4: on the browser side. As an area of focus for
Speaker 4: agent Tachai is that something you feel is very important
Speaker 4: to roll out the agents.
Speaker 2: So some companies try to go and buy many companies
Speaker 2: to create a collection of things. We are very focused
Speaker 2: on what we want. We are focused on zero trust
Speaker 2: and then we focused on AI. Regarding observability, we actually
Speaker 2: do observability for the areas that matter to our customers.
Speaker 2: We sit between the user and the application. So today
Speaker 2: we have a size business, hundreds of millions of dollar
Speaker 2: business with the product we call z Skinnar Digital Experience,
Speaker 2: where we can tell our customers if any user is
Speaker 2: having any performance issues as they try to access those applications.
Speaker 2: It's integrated with a platform. While many companies have many
Speaker 2: point products and they are separate, we like to have
Speaker 2: integrated platform that serves our customers. So we not only
Speaker 2: provide secure and reliable experience, we make sure that it
Speaker 2: is fast and you can trouble shoot those things. But
Speaker 2: I'm not going into broad observability, which has become a
Speaker 2: broad area. We are focused on the areas that are
Speaker 2: relevant to our customers.
Speaker 4: And identity is that something you care about? The identity
Speaker 4: on the browser.
Speaker 2: Identity is important. Think about identity for users. We have
Speaker 2: been working from day one with all leading ID provider
Speaker 2: for users or whether it's Microsoft and oct and others. Now,
Speaker 2: when it comes to identity of agents, I believe there'll
Speaker 2: be many contenders Microsoft, Google, Aws octors of the world.
Speaker 2: Our philosophy is to federate those identity providers use that
Speaker 2: identity and we are the zero trust exchange, the switchboard
Speaker 2: to make sure the right AI agent talks to right
Speaker 2: agent in this world. I do not need to own everything.
Speaker 2: I need to do some of the things I do
Speaker 2: the best and integrate with partners with proper API integration
Speaker 2: so our customers get the biggest benefit. We believe in
Speaker 2: doing a few things, but do them extremely well and
Speaker 2: partner with others.
Speaker 3: So I do feel like we're all learning as we go.
Speaker 3: And of course man Deep and Jay, you guys are
Speaker 3: ahead of us in a big way. But when they
Speaker 3: talk Man Deep about zero trust is never trust, always verify.
Speaker 3: I think about digital touch points thinking that there are
Speaker 3: threats within an organization and outside, and you've got to
Speaker 3: make sure there's security everywhere.
Speaker 4: Yeah, no matter where you are, and that's where you know.
Speaker 4: Sase is a term that gets thrown a lot, and
Speaker 4: z scaler is in the leading position in that magic quadrant.
Speaker 4: So I have one other question Jay for you. So,
Speaker 4: given the amount of data in the world of security,
Speaker 4: and you know you guys generate trillions of data points,
Speaker 4: will the security world have its own.
Speaker 2: Lell Yes, the answer is yes. We are actually working
Speaker 2: on building our security focus LM, and I do not
Speaker 2: need to have the large large language model. Security is
Speaker 2: very focused set of high equality data. With over eight
Speaker 2: thousand customers and forty five percent of Fortune fire and companies,
Speaker 2: we generate over half for trillion transaction logs a day.
Speaker 2: Those logs are anonymized, but they can give us an
Speaker 2: idea of where the threats are coming from. We can
Speaker 2: find a needly hoistag and help all of our customers.
Speaker 2: So AI is only as good as the data that
Speaker 2: powers it, and we have the best data and we
Speaker 2: believe we can help identify some of these threats in
Speaker 2: almost near real time and provide a closed loop system
Speaker 2: so that the threats can't really exploit our customers and
Speaker 2: provide them benefit at a much faster ways. That's why
Speaker 2: we have focused on AI powered security operations, and our
Speaker 2: acquisition of redcnnety is part of the strategy because they
Speaker 2: build some very very good, egenic AI technology that we're
Speaker 2: integrating with our platform.
Speaker 1: The use of AI to make the system more robust
Speaker 1: certainly makes sense, but I got to tell you min
Speaker 1: deeper and I are actually moderating some panels next week
Speaker 1: at a Bloomberg Live event that's focused on cybersecurity, and
Speaker 1: in the prep that we're doing for that, what I
Speaker 1: keep hearing from these chief security office, from these chief
Speaker 1: information security officers, is the concern about how AI has
Speaker 1: made the attackers just more robust and the attacks more robust.
Speaker 1: Can you point to specific instances where hackers have actually
Speaker 1: used AI to enhance their attacks and did it work?
Speaker 2: Yes, there are many many examples. Let me give you
Speaker 2: a few simple ones. Every attack starts by finding your
Speaker 2: attack surface, who where you are and public IP address
Speaker 2: is the starting point. Every firewall, every VPN, every application
Speaker 2: portal is an attack surface. In the past, a hacker
Speaker 2: may have taken weeks to identify it. Now you can
Speaker 2: go to chat GPT and say tell me all the
Speaker 2: firewalls and VPNs that have won abilities and give it
Speaker 2: to me in a nice tabler format. Under sixty seconds,
Speaker 2: you can get that now. The second part attackers would
Speaker 2: do is these phishing emails. Now they can ask AI
Speaker 2: to say, write an email that looks like a cfo's
Speaker 2: writing style, no typos, make it very targeted. That's number two. Third,
Speaker 2: hackers are using automation that AI provides. Once they are
Speaker 2: on the network, automation can find the key applications and
Speaker 2: try to encrypt that data. A lot of that is happening.
Speaker 2: What does these kin do in this case? Number one,
Speaker 2: we hide your attack surface. Your applications are hidden behind
Speaker 2: our cloud. Bad guys can even find you. They can't
Speaker 2: find you, they can attack you. And the second is
Speaker 2: on the network. The biggest problem with firewalls and vpnss. Right,
Speaker 2: they're trying to protect the castle, and we actually make
Speaker 2: it zero. Trust.
Speaker 3: Jay, We've got to run. This was so informative and
Speaker 3: so enlightening in terms of AI security. We so appreciate it.
Speaker 3: Jay Toddray is founder, chairman's eeoz Scaler and of course
Speaker 3: our own Mandi saying a va