Glow, AI endpoint security startup, raises $180M at $1.2B valuation

Glow, a Palo Alto-headquartered cybersecurity startup, emerged from stealth on Wednesday with a $180 million（約290億円） Series A funding round that values it at $1.2 billion（約1900億円）. The round was led by Sequoia Capital, Cyberstarts, Greenoaks, and Redpoint Ventures, with participation from Index Ventures, Swish Ventures, Lux Capital, Operator Collective, and Holly Ventures. The investment makes Glow one of the latest cybersecurity startups to achieve unicorn status before publicly disclosing revenue metrics.

Founded in 2025, Glow was built by a team of veterans from major tech and security firms. Co-founder and CEO Roi Tiger is a former Meta vice president of engineering. He is joined by Omer Singer, former cybersecurity strategy head at Snowflake; Ophir Arie, former vice president of research and development at Claroty; and Arnon Joseph, a former Meta engineering leader. The leadership team also includes COO Emily Heath, a former chief information security officer at United Airlines and Docusign who served on the board of Wiz through its $32 billion（約5.1兆円） acquisition by Google and was previously a partner at Cyberstarts.

The startup has built an endpoint security platform designed to help enterprises monitor and control the software, AI agents, and developer tools running on employee devices. The platform uses specialized AI agents to continuously map enterprise environments, assess risk in real time, and enforce security policies. To power it, Glow leverages AI models from Anthropic and Google's Gemini through Amazon Bedrock, while building its own software to provide context to those models and improve their reliability for security tasks. According to Tiger, the platform has already prevented malicious npm packages from being installed in customer environments, identified AI agents attempting to pull in such software, and detected employee devices where endpoint detection and response tools were missing or operating with reduced functionality.

Even though Glow has just emerged from stealth, the company said it already has paying customers across healthcare, retail, and financial services. The startup declined to disclose customer names and numbers, but Tiger said typical deployments span tens of thousands of employee devices across global organizations. Glow employs nearly 100 people, about 70% of whom are based in Israel and the remainder in the U.S.

Glow's approach targets a gap it sees in the existing endpoint security market, which is dominated by CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks. Tiger argued that existing endpoint detection and response products focus primarily on detecting threats after they emerge, whereas Glow is designed to prevent risky software, AI agents, and developer tools from entering enterprise environments in the first place. This preventive stance responds to a broader industry shift: as enterprises deploy AI tools and attackers increasingly use generative AI to automate phishing, develop malware, and launch more sophisticated cyberattacks, companies are rethinking how they secure endpoints—from employee laptops to servers and other connected devices. Concerns have intensified since Anthropic unveiled its Mythos AI model, which demonstrated advanced capabilities in identifying and exploiting software vulnerabilities. Tiger framed Glow's mission in this context, saying: "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."

Glow's emergence reflects a fundamental shift in enterprise security priorities driven by the rapid deployment of AI tools across organizations. The startup's founders—drawn from Meta, Snowflake, and Claroty—bring deep expertise in both engineering and cybersecurity, signaling that this is not a me-too play in an established market but a deliberate response to a new threat landscape. The company's ability to raise $180 million（約290億円） at a $1.2 billion（約1900億円） valuation before public disclosure of revenue or customer counts suggests strong investor confidence that AI-native endpoint security represents a genuine category shift, not an incremental feature addition.

The timing is acute: as the article notes, concerns have intensified since Anthropic unveiled its Mythos AI model, which demonstrated advanced capabilities in identifying and exploiting software vulnerabilities. This has prompted broader debate over AI-assisted cyberattacks, making the case for preventive tools that stop malicious software and AI agents before they enter enterprise networks. Glow's platform uses specialized AI agents to continuously map environments and assess risk in real time—a proactive stance that contrasts with legacy endpoint detection and response tools built for a pre-AI threat model.

Glow enters a crowded market dominated by established players like CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks, but the startup's focus on prevention rather than detection positions it as an orthogonal offering rather than a direct replacement. Whether this becomes a distinct, durable category depends on enterprise adoption patterns—and that question remains open, as the article notes, since enterprises are only beginning to grapple with the security implications of increasingly capable AI models.

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