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

UPDATED 06:00 EDT / JULY 22 2026 SECURITY AI-native endpoint security startup Glow is born a unicorn after raising $180M by Mike Wheatley 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