Netskope, Inc. Class A Common Stock 2027 Q2 Earnings Call

Please go ahead. Good afternoon, and thank you for joining us today.

With me on the call are Netskope CEO and Co-founder, Sanjay Beri, and CFO, Drew Del Matto. The press release announcing our financial results for the second quarter of fiscal 2027 was issued earlier today and is posted to our investor relations website at investors.netskope.com, along with the supplemental presentation. Before we begin, let me remind everyone that certain statements we make on today's call are forward-looking, including statements related to our guidance for the third quarter and full 2027 fiscal year, market opportunity, growth prospects, sales ramping, competitive position, impact of AI, and demand for AI security. These forward-looking statements are subject to known and unknown risks and uncertainties, which could cause actual results to differ materially from those anticipated by these statements.

Additionally, these statements apply only as of today, and we undertake no obligation to update them in the future. For a detailed description of risks and uncertainties, please refer to our SEC filings as well as our earnings press release. Finally, unless otherwise noted, all financial metrics we discuss on this call, other than revenue, will be on an adjusted non-GAAP basis. We have provided reconciliations of these non-GAAP financial measures against the most directly comparable GAAP financial measures in our earnings press release. Now let me turn the call over to Sanjay to discuss our business momentum and highlights from our Q2 financial performance.

Sanjay. Thanks, Michelle. We had a strong second quarter with our results reflecting durable demand for Netskope's highly differentiated platform.

In the age of AI, security and network modernization have become inseparable, and businesses can no longer afford to trade security for performance. As enterprises embrace AI and cloud, they need a modern architecture that understands the context and intent of today's internet, cloud, and AI environments. This architecture must protect massive amounts of transactions and data spanning thousands of cloud and private applications and data stores, billions of websites and other destinations, and a vast set of commercial and open-weight AI apps and models. It must inspect and control traffic in real time, at high speed, and with data sovereignty.

The need for this architecture is becoming even more acute as the volume and velocity of transactions and data, and the number of humans and AI agents originating these transactions and operating on data grows exponentially. Netskope uniquely delivers this modern, scalable, resilient, and sovereign real-time architecture through the combination of our Netskope One platform and NewEdge private cloud network. This is why customers are choosing us as the trusted partner to help them say yes to AI. They want to capture the enormous potential of one of the most defining technologies of our lifetime without compromising security, performance, or control. This positions us exceptionally well to address a massive $170 billion greenfield opportunity in AI security within our $336 billion total addressable market. I will come back to that in a moment. First, a few highlights from the quarter.

We ended Q2 with ARR of $899 million, up 27% year-over-year, and delivered net new ARR of $54 million. Revenue grew 29% year-over-year to $221 million ahead of our guidance, and our net retention rate, or NRR, increased to 114%. Our outperformance flowed through to the bottom line, with our operating margin improving 11 percentage points year-over-year to negative 9%, significantly ahead of our guided range. Demand for our Netskope One platform of 25-plus security networking, analytics, and AI products remains strong as enterprises continue to modernize their infrastructure for the AI era. We were particularly encouraged by the traction from our recently announced AI security suite. While it is still early, we are seeing strong customer engagement and rapid pipeline generation for these products, with some deals closed and many more currently in the proof of concept or POC stage.

Enterprises globally remain strategically focused on modernizing their security and infrastructure. We are using technology sprawl, protecting sensitive transactions and data, ensuring data sovereignty, and of course, safely using AI. A hot topic in my daily dialogues with CXOs is the fact AI creates exponentially more transactions and data and a much more complex attack surface, and how modernization and AI adoption go hand in hand. The Mythos moment this past spring underscored just how quickly the landscape is changing. The pace of innovation across frontier models and increasingly capable open-weight models is accelerating the ability to discover vulnerabilities and strengthen defenses at AI speed. But that same acceleration works both ways. These models are also lowering the barrier for attackers, compressing the time from discovery to exploitation, and expanding the attack surface, not only through human adversaries, but increasingly through autonomous AI agents operating at machine speed.

We are already seeing this play out with AI agents escaping isolated environments, exploiting vulnerabilities, escalating privileges, moving laterally, and stealing credentials, even when they were not explicitly instructed to attack. They were simply asked to complete a cybersecurity benchmark, and when the intended route proved difficult, found another path to the answer. This is perhaps the clearest example yet of cyber risk extending beyond human attackers leveraging AI. Malicious intent is no longer the security threshold. An agent does not need to be prompted to be a bad actor. Instead, a stated task, enough autonomy in an environment that can be circumvented can be enough to do damage. All this reinforces that rogue agent risk is not an isolated incident or a mishap. It is a real and emerging control risk that CISOs face today and considerably broadens the security problem.

This is why AI security is becoming such a critical priority for enterprises. The challenge is no longer simply how to secure AI models or prevent employees from using AI. It is how to give enterprises the visibility, control, protection, and performance they need as AI becomes deeply embedded across their people, applications, data, and increasingly autonomous agents. I have had more than 100 conversations with customers this quarter, and in almost every one of them, a CISO or CIO comes back to the same question: how do we move faster with AI without losing control? Security, IT, and infrastructure leaders don't want to say no to using AI. They want to say yes to it, but do so safely. Let me share a few challenges they are facing and how Netskope is helping solve it. First, let's start with visibility.

The majority of customers I talk to about AI security do not know what or how AI models and applications are being used, what corporate data is being fed into them, where agents are in their organization, what they have access to, and what they are doing. Netskope's platform solves this problem by allowing companies to answer the question of what AI am I using, including providing full visibility into agentic and MCP traffic via our Agentic Broker. It bridges the gap between human or agent and LLM interactions or machine-to-machine workflows. Agentic Broker has been a natural starting point for customers securing AI and a game changer as they tackle unsanctioned and unmonitored AI usage in their organizations.

In addition, our recently released AI Command Center provides customers with a unified, real-time, continuous, and correlated view of where their AI risk is and makes policy and remediation recommendations that help them act on it. The second issue customers are grappling with is how to put the right defense layer around AI to prevent AI-specific threats like prompt injection and jailbreaking, and to ensure models adhere to company policy, preventing misuse or unwanted responses. Imagine a scenario where an adversary attempts to override system rules through a multi-turn attack in order to exfiltrate data. Our AI Guardrails solution is designed precisely to help customers address this. In addition, our AI Gateway secures API traffic between private applications, autonomous agents, and LLMs, and can be deployed on premises or in the cloud.

Third, customers need a highly performing network that can handle the exceptional volume of AI transactions and data, and the growing amount of highly interactive, latency-sensitive agentic communications while ensuring they are adhering to strict regulations, including data sovereignty. Our NewEdge private cloud spans more than 120 data centers around the globe, and we operate all our products in our unified platform at each location, creating distinct performance and sovereignty advantages. NewEdge also allows customers to define geo-based policies to control exactly where their AI security and networking processing occurs, giving them sovereignty over their transactions and data wherever it lives or flows. Customers are seeing that today's AI environment has become a watershed moment for security. AI security-related pipeline is growing at a rapid pace, and deals are moving into proof-of-concept phases.