AI-native endpoint security startup Glow is born a unicorn after raising $180M

AI-native endpoint security startup Glow is born a unicorn after raising $180M Glow Security Inc. said today it’s exiting stealth mode today as an instant unicorn after closing on a massive $180 million Series A funding. The round catapults the startup’s valuation to a stunning $1.2 billion right out of the gate. Venture capital firms Sequoia, Cyberstarts, Greenoaks and Redpoint Ventures co-led the round, which also saw the participation of Index Ventures, Lux Capital, Swish Ventures and Holly Ventures. The funds will enable Glow to expand Glow Labs, its dedicated research organization, launch its first products and accelerate its go-to-market operations. Glow said it’s trying to fix what is fast becoming a major crisis for enterprise security teams. It’s trying to address the massive explosion of artificial intelligence applications, tools and systems running on corporate endpoints, which has created an unprecedented cybersecurity challenge. As businesses eagerly embrace AI chatbots, assistants and autonomous agents and use them to perform increasing amounts of work, they’re leaving themselves exposed to all kinds of risks. The problem is that their security teams simply can’t keep up, and have no way to vet all of these AI tools fast enough. The startup offers a single, but compelling, datapoint to back up its claims, saying that regular AI usage on corporate devices has increased from 15% to more than 45% in less than a year. Glow believes that this explosive rate of adoption is leaving organizations at the mercy of an entirely new class of endpoint risks that they’re totally unprepared for. Their existing endpoint security tools were never designed for AI, as they’re more focused on reacting to threats when they pop up. But with cyberattackers now having access to powerful AI tools themselves, they can create systems that can potentially discover vulnerabilities and design ways to exploit them almost instantly. “AI has created an entirely new attack surface that security teams are just beginning to understand,” Glow Chief Operating Officer Emily Heath told SiliconANGLE. “AI has changed how technology enters the enterprise in ways we haven’t seen before, because employees can now start using new tools and connecting agents, plugins and packages to company data much faster than traditional approval process were designed to handle.” Heath said enterprises face three broad categories of risk that simply didn’t exist before. These include the threat of “shadow AI,” which is when employees use personal or free AI tools that live outside of corporate governance controls, leaving to uncertainty over where sensitive data might be stored and how it might be used. A second major risk pertains to the configuration of AI systems. Though most AI applications do have security controls such as permission settings, execution restrictions and isolation features, most organizations lack a way to manage them consistently at scale across thousands of endpoints. “There’s also the connected ecosystem risk,” Heath revealed. “Modern AI tools rarely operate alone, connecting to plugins, packages, MCP servers and other services to expand what they can access and do, and this ecosystem is evolving faster than what most security teams can track manually.” A new approach to endpoint security There are so many risks surrounding AI that in the event something goes wrong, most businesses probably won’t even know what hit them. And this is precisely why a new kind of endpoint security operating model is so badly needed, Heath said. Instead of being reactive, security teams must become proactive and shut down threats before they’re ever identified and exploited. This is where Glow comes in. It has created an AI-native endpoint security platform that’s designed for proactive risk prevention. It gives security teams full control over everything that executes on corporate endpoints by deploying specialized AI agents that continuously map their environments and analyze risk in real time. The startup’s co-founder and Chief Executive Roi Tiger stressed that prevention has always been the best way to secure endpoints, but it hasn’t really been possible before. “Prevention never worked at enterprise scale without blocking the business,” he explained. “But AI solves that. The moment we saw what AI made possible, we knew the endpoint could finally be protected in the way it always should have been.” Rather than wait for a threat to emerge, Glow relies on its advanced reasoning engine to automatically enforce security policies across every endpoint. The agents proactively decide which applications and tools should be allowed to run on an endpoint, and which should be shut down. What’s especially important is the speed at which its agents operate. According to Heath, they’re able to make these complex decisions at lightning speed, so they don’t slow down employees’ work or disrupt business processes. Heath explained that the secret to this speed is the lightweight design of its AI agents. Rather than run on the endpoint itself, which would likely impact the performance of user’s devices, they instead run on Glow’s centralized servers. “Endpoint data is pulled into Glow, where all of the analysis, reasoning and policy decisions are made by over a hundred different specialized agents,” she explained. “That architecture minimizes the impact on end-user devices.” It also helps address the plague of false positives that is prevalent on legacy endpoint security tools, Heath said. She explained that the problem with legacy tools is that they tend to evaluate individual events in isolation, because they lack broader context of the endpoint’s history. Glow’s agents work differently, she said, creating a continuously updated understanding of the endpoint, the software running on it, the owner of the devices, the people who use it, what programs they’re using, how they’re using those tools and the other devices and services it’s connected to. This information is stored in Glow’s cloud and enriched with external intelligence about the reputation of software vendors, known risks and user’s and organization’s privacy practices. “We also reconcile the data from multiple enterprise systems into a single view,” Heath said. “Because our agent’s decisions are based on that broader context rather than a single signal or rule, Glow can make much more informed recommendations and reduce the false positives that have historically made prevention so difficult.” Glow said its platform has been a big hit with early adopters in industries spanning retail, healthcare and financial services. The confidence of Glow’s impressive roster of backers is primarily a testament to the pedigree of its founders and executive team. Tiger’s co-founders include Chief Technology Officer Omer Singer and Vice President of Research and Development Ophir Arie. Singer is the former head of cybersecurity strategy at Snowflake Inc., while Arie previously served in the same role at Claroty Inc. As for Tiger, he spent nine years at Meta Platforms Inc., most recently serving as its vice president of engineering, prior to starting Glow. Other top executives include Chief Product Officer Arnon Joseph, who is a former senior director of product at Meta and a two-time founder himself, and Heath, who previously served as the chief information security officer at United Airlines Inc. and DocuSign Inc., and also sat on the board of Wiz Inc. prior to its acquisition by Google LLC. “I sat in the CISO seat for a long time, and I can tell you that the tools available to us were never built for what enterprises face today,” Heath said. “There is now an entirely new class of risk to manage.” Image: SiliconANGLE/Microsoft Designer A message from John Furrier, co-founder of SiliconANGLE: Support our mission to keep content open and free by engaging with theCUBE community. 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