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    Home»Business»Glow Endpoint Security Startup Raises $180m at $1.2bn Unicorn Valuation
    Glow endpoint security
    Business

    Glow Endpoint Security Startup Raises $180m at $1.2bn Unicorn Valuation

    Funke AdeyemiBy Funke Adeyemi28/07/2026No Comments4 Mins Read
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    Glow endpoint security has stepped out of stealth with $180 million in funding and a $1.2 billion valuation, making it one of the handful of cybersecurity startups to achieve unicorn status before disclosing a single revenue figure.

    The Palo Alto company closed an all-equity Series A backed by Sequoia Capital, Cyberstarts, Greenoaks, and Redpoint Ventures, with Index Ventures, Swish Ventures, Lux Capital, Operator Collective, and Holly Ventures also participating. One Israeli financial outlet, Calcalist Tech, described the raise as a $100 million Series B that brought cumulative funding to $180 million across three earlier rounds; Glow’s own press release characterises the full $180 million as its Series A, and that figure is the one the company stands behind.

    Why the Timing: AI Is Landing on the Endpoint

    The founding premise is simple enough to state, harder to solve. Enterprises spent the past decade migrating workloads to the cloud, building their security stacks around that model. Then generative AI arrived on employee devices, on developer laptops, inside coding assistants and autonomous agents, and the perimeter shifted again.

    ‘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 Roi Tiger, Glow’s co-founder and chief executive, in an interview.

    The numbers point in one direction. According to Tech Funding News, reporting on Glow’s market rationale, unauthorised AI use on corporate devices jumped from 15% to 45% over the past year. Meanwhile, Anthropic’s recently unveiled Mythos AI model demonstrated advanced capabilities in identifying and exploiting software vulnerabilities, intensifying debate about AI-assisted cyberattacks.

    Glow’s response is a platform that maps enterprise environments continuously, assesses risk in real time, and uses specialised AI agents to enforce security policies before threats materialise, rather than detecting them afterward. Tiger argues that existing endpoint detection and response products from CrowdStrike, Microsoft, SentinelOne, and Palo Alto Networks are built around the reactive model: spot the threat after it appears. Glow’s pitch is prevention: keep risky software, AI agents, and developer tools out of the environment in the first place.

    The platform has already blocked malicious npm packages from being installed in customer environments, identified AI agents attempting to pull in unauthorised software, and flagged employee devices where endpoint detection and response tools were missing or degraded, Tiger said. Deployments typically span tens of thousands of devices across global organisations.

    Glow Endpoint Security’s Founding Team and Investor Backing

    Tiger spent nine years at Meta, finishing as VP of Engineering. He is also a co-founder of Onavo, the mobile analytics company. His co-founders are Omer Singer, who serves as CTO and previously led cybersecurity strategy at Snowflake; Ophir Arie, formerly VP of Research and Development at Claroty; and Arnon Joseph, Glow’s Chief Product Officer, who brought eight years at Meta as Senior Director of Product. The four founded the company in 2025.

    Rounding out the leadership is chief operating officer Emily Heath, 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. Heath was also previously a partner at Cyberstarts, one of Glow’s lead investors.

    Sequoia Capital partner Shaun Maguire led the firm’s investment. ‘Partnering with Roi, Omer, and Ophir was one of the easiest decisions we’ve made. This is a team that has built and operated at a massive scale, going after a problem that will define the industry,’ Maguire said.

    Cyberstarts founder Gili Raanan struck a similar note, saying: ‘Great companies are ultimately defined by the people who build them. Roi, Omer, Ophir, Arnon and Emily have assembled an extraordinary group of builders with the talent and determination to create something enduring,’ according to Help Net Security.

    What the Money Is For

    According to Glow’s official press release, the $180 million will fund two priorities: expanding its go-to-market team in the United States and growing Glow Labs, the company’s in-house cybersecurity research division.

    The startup already has paying customers across healthcare, retail, and financial services, though it declined to name them or disclose their count. It employs nearly 100 people, with roughly 70% based in Israel and the remainder in the United States. The platform runs AI models from Anthropic and Google’s Gemini through Amazon Bedrock, alongside proprietary software built to supply the models with enterprise context and sharpen their reliability for security tasks.

    The category Glow is staking out, AI-native endpoint security, does not yet exist as a distinct market segment. Whether CIOs carve out a separate budget line for it, or whether incumbents absorb the capability into their existing platforms, is the question that will determine whether Glow’s unicorn price tag was prescient or premature. The answer will probably arrive before the next funding round does.

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    Funke Adeyemi

    Funke Adeyemi spent a decade in corporate banking and fintech before moving to business journalism. She started in trade finance at a major UK bank, moved to a payments company scaling into African markets, and spent her last role leading partnerships at a cross-border remittance platform. She writes about business strategy, fintech, digital banking, and the corporate news that moves markets. She is interested in how companies actually make money rather than how they describe making money in investor presentations. Funke lives in South London. She reads earnings calls the way other people listen to podcasts, and finds them about as reliable.

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