The $1.2B Bet on AI-Native Endpoint Security
Glow just emerged from stealth with a $1.2 billion valuation and an $180 million Series A, but the story isn't really about the money. It's about a bet that the endpoint—the employee laptop, the server, the connected device—has become the most dangerous place in enterprise IT. And nobody else is building for it yet.
Palo Alto-headquartered Glow raised this round from a who's who of Silicon Valley venture firms: Sequoia Capital, Cyberstarts, Greenoaks, and Redpoint Ventures led, with participation from Index Ventures, Swish Ventures, Lux Capital, Operator Collective, and Holly Ventures. Founded in 2025, Glow is one of the latest cybersecurity startups to hit unicorn status without publicly disclosing revenue. That's not unusual anymore. What's unusual is what they're actually selling.
Why the Endpoint Is Back in the Crosshairs
For most of the past decade, enterprise security chased the cloud. SaaS sprawl, remote work, hybrid infrastructure—everyone moved the perimeter off-site. Endpoint detection and response (EDR) became an afterthought, a checkbox on the compliance list.
Then AI landed on the endpoint in a way we've never seen before.
Developers started deploying localized AI agents directly onto employee machines. These aren't simple chatbots. They're autonomous tools that interact with codebases, sensitive data, and internal systems, often operating without the granular oversight that IT and security teams expect. And attackers noticed.
Anthropic's recent unveiling of its Mythos AI model—designed to identify and exploit software vulnerabilities—sent shockwaves through the security community. The model demonstrated advanced capabilities in vulnerability exploitation, sparking a broader debate about AI-assisted cyberattacks. When attackers can use generative AI to automate phishing, develop malware, and identify vulnerabilities at scale, reactive security is dead.
Glow is betting that this shift demands a fundamentally different approach.
How Glow Actually Works
Glow's platform uses specialized AI agents to continuously map enterprise environments, assess risk in real time, and enforce security policies. Here's the technical architecture: Glow leverages Amazon Bedrock to run AI models from Anthropic and Google's Gemini, but the real value is in the software layer Glow built on top of these models.
A raw AI model doesn't understand your organization's internal security policies, your unique risk tolerance, or your specific compliance requirements. Glow's platform wraps these foundational models with enterprise context, turning them into proactive security auditors rather than generic intelligence tools.
The results are already showing up in production environments. Glow has prevented malicious npm packages—those third-party software components that every application depends on—from being installed in customer environments. The platform has identified AI agents attempting to pull in unauthorized third-party software. It has flagged employee devices where EDR tools were either missing or operating with reduced functionality.
This is a crucial distinction. Companies like CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks remain industry leaders in detecting threats after they emerge. Glow is making a high-stakes bet that the future belongs to platforms designed to prevent risky software, AI agents, and developer tools from entering enterprise environments in the first place.
The Team Behind the Platform
Glow's founding team reads like a who's who of modern tech leadership. CEO and co-founder Roi Tiger, a former Meta vice president of engineering, assembled a group of executives from some of the most consequential companies in enterprise software.
Omer Singer, former Snowflake cybersecurity strategy head, brings deep enterprise infrastructure experience. Ophir Arie, formerly Claroty's vice president of research and development, contributes critical industrial IoT security expertise. Arnon Joseph, a former Meta engineering leader, rounds out the technical founding team.
On the operations side, Glow brought in Emily Heath as Chief Operating Officer. Heath is a former CISO at both United Airlines and Docusign, and she served on the board of Wiz through its $32 billion acquisition by Google. She was also previously a partner at Cyberstarts, one of Glow's lead investors.
That board seat at Wiz—through a $32 billion deal that redefined enterprise security valuations—gives Heath institutional credibility in navigating the enterprise sales cycle. She's seen what happens when security companies scale to massive valuations. She's advising Glow on how to avoid the common pitfalls.
Where Glow Is Deployed—and Where It's Headed
Glow has paying customers across healthcare, retail, and financial services. The company declined to disclose specific customer names, but CEO Roi Tiger told TechCrunch that typical deployments span tens of thousands of employee devices across global organizations.
The company employs nearly 100 people. About 70% are based in Israel, with the remainder in the U.S. This geographic distribution—common among Israeli-founded tech startups—gives Glow access to deep engineering talent while maintaining proximity to Silicon Valley's venture ecosystem.
Whether AI-native endpoint security becomes a distinct category remains an open question. Enterprises are only beginning to grapple with the security implications of increasingly capable AI models. Over the next eighteen months, the market will decide if Glow has created a new category or simply rebranded existing endpoint security with AI buzzwords.
For now, the $1.2 billion valuation is a clear signal: the endpoint, once considered a solved problem, is once again the hottest battlefield in cybersecurity.
