Glow Emerges From Stealth at $1.2B to Redefine Endpoint Security for the AI Era

Why Now, and Why Endpoints

The timing isn’t accidental. Enterprises are deploying AI tools at scale, and attackers are using generative AI to automate phishing campaigns, develop malware faster, and probe for vulnerabilities with less human effort.

The debate sharpened when Anthropic unveiled its Mythos AI model, which the company said demonstrated advanced capabilities in identifying and exploiting software vulnerabilities. That disclosure accelerated a broader conversation about what AI-assisted cyberattacks could look like at scale — and whether existing defenses are equipped to handle them.

“If you think of the past decade, everything was moving to the cloud and SaaS. Suddenly, AI lands on the endpoint in a way we’ve never seen,” said co-founder and CEO Roi Tiger.

Tiger is a former Meta VP of Engineering. His co-founders bring similarly dense credentials: Omer Singer, former cybersecurity strategy head at Snowflake; Ophir Arie, former VP of R&D at Claroty; and Arnon Joseph, another former Meta engineering leader. Chief Operating Officer Emily Heath previously served as CISO at United Airlines and DocuSign, sat on the board of Wiz through its $32 billion acquisition by Google, and was a partner at Cyberstarts.

What Glow Actually Does

Glow’s platform is designed to monitor and control the software, AI agents, and developer tools running on employee devices across an enterprise. It uses specialized AI agents to continuously map environments, assess risk in real time, and enforce security policies — before threats take hold rather than after.

In practice, the platform has already:

• Blocked malicious npm packages from being installed in customer environments
• Identified AI agents attempting to pull in risky third-party software
• Detected employee devices where endpoint detection and response tools were missing or running with reduced functionality

Glow uses AI models from Anthropic and Google’s Gemini via Amazon Bedrock, while building its own software layer to give those models enterprise context and improve reliability for security-specific tasks.

Typical deployments span tens of thousands of devices across global organizations. The startup says it already has paying customers in healthcare, retail, and financial services — though it declined to name them or share customer counts.

The Crowded Market It’s Walking Into

Endpoint security is not a greenfield opportunity. CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks all have significant market share and deep enterprise relationships.

Tiger’s argument is that existing endpoint detection and response (EDR) products are fundamentally reactive — built to detect threats after they emerge. Glow is positioning itself as preventive: stopping risky software, AI agents, and developer tools from entering enterprise environments in the first place.

That’s a meaningful distinction, but it’s also a claim that will need to hold up under real-world enterprise scrutiny. Whether AI-native endpoint security becomes a recognized category of its own, or gets absorbed into broader platform plays by incumbents, remains an open question.

The Team and Scale

Glow employs nearly 100 people, with roughly 70% based in Israel and the rest in the U.S. — a structure common among cybersecurity startups with deep technical roots in Israeli security research.

The company’s leadership team has direct experience across enterprise security, cloud infrastructure, and AI — which matters in a space where credibility with CISOs is often the first barrier to entry.

What to Watch

Glow’s emergence is a useful signal for anyone tracking the enterprise security landscape. The convergence of AI agents running on employee devices, generative AI-powered attacks, and increasingly capable AI models is creating real gaps that legacy EDR tools weren’t designed to address.

Whether Glow fills those gaps better than incumbents who are also rapidly adding AI capabilities — that’s the question worth watching over the next 12 to 18 months. For now, the funding, the team, and the early customer traction suggest this is a startup worth keeping on your radar.