Glow, a cybersecurity startup founded by former Meta and Snowflake executives, has emerged from stealth as a unicorn, betting that artificial intelligence is reshaping how enterprises secure employee devices.
The Palo Alto-headquartered company announced on Wednesday it raised $180 million in an all-equity Series A funding round. This investment valued the firm at $1.2 billion. Backers include Sequoia Capital, Cyberstarts, Greenoaks, and Redpoint Ventures. Index Ventures, Swish Ventures, Lux Capital, Operator Collective, and Holly Ventures also participated.
This capital injection makes Glow one of the latest cybersecurity startups to achieve unicorn status before publicly disclosing revenue metrics.
As more enterprises deploy AI tools, attackers increasingly use generative AI to automate phishing, develop malware, and launch more sophisticated cyberattacks. Companies are rethinking how they secure endpoints, ranging from employee laptops to servers and other connected devices. Concerns have intensified since Anthropic unveiled its Mythos AI model, which the company said demonstrated advanced capabilities in identifying and exploiting software vulnerabilities. This development prompted broader debate over AI-assisted cyberattacks. Glow is betting that this shift requires a new approach to endpoint security.
The new platform
Founded in 2025, Glow is building an endpoint security platform that helps enterprises monitor and control the software, AI agents, and developer tools running on employee devices. The startup said the platform uses specialized AI agents to continuously map enterprise environments, assess risk in real time, and enforce security policies.
“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,” co-founder and chief executive Roi Tiger said in an interview.
Tiger, a former Meta vice president of engineering, co-founded Glow alongside former Snowflake cybersecurity strategy head Omer Singer, former Claroty vice president of research and development Ophir Arie, and former Meta engineering leader Arnon Joseph. The startup’s leadership team also includes chief operating officer Emily Heath. She is a former chief information security officer at United Airlines and DocuSign who served on the board of Wiz through its $32 billion acquisition by Google and was previously a partner at Cyberstarts.
Even though it has only just emerged from stealth, Glow said it already has paying customers across industries including healthcare, retail, and financial services. The startup declined to disclose customer names and numbers. Tiger noted that typical deployments span tens of thousands of employee devices across global organizations.
To power the platform, Glow uses AI models from Anthropic and Google’s Gemini through Amazon Bedrock. The company builds its own software to provide the models with enterprise context and improve their reliability for security tasks, Tiger told TechCrunch.
Glow’s platform has already prevented malicious npm packages, third-party software components used to build applications, from being installed in customer environments. It has 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.
Glow enters a crowded endpoint security market dominated by companies including CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks. Tiger said existing endpoint detection and response products focus primarily on detecting threats after they emerge. Glow is designed to prevent risky software, AI agents, and developer tools from entering enterprise environments in the first place.
The startup employs nearly 100 people. About 70% of the workforce is in Israel, with the remainder in the U.S. Whether AI-native endpoint security platforms become a distinct category remains to be seen, as enterprises are only beginning to grapple with the security implications of increasingly capable AI models.
What it means
For businesses managing remote workforces, this funding signals a shift from reactive monitoring to proactive prevention. Existing tools often struggle to distinguish between legitimate developer workflows and malicious activity once code is on a device. Glow aims to solve this by using AI to understand the context of what is running on a machine before it causes harm. This approach could reduce the noise in security alerts while catching threats that traditional signature-based systems miss. However, the market remains uncertain about whether this specific angle will stick or if it is simply a niche feature for the next generation of endpoint protection.
