Glow Raises $180M to Rebuild Endpoint Security for the AI Era

Enterprise devices are filling up with AI assistants, software agents and new applications faster than security teams can approve them.

That pace creates a basic visibility problem: organizations cannot protect what they do not know is running.

Glow has emerged from stealth with $180 million in funding at a $1.2 billion valuation to build an endpoint security platform designed around prevention rather than incident response. The financing was led by Sequoia Capital, Cyberstarts, Greenoaks and Redpoint Ventures.

The round also included Index Ventures, Swish Ventures, Holly Ventures, Operator Collective and Lux Capital.

Founded by CEO Roi Tiger, CTO Omer Singer and VP of R&D Ophir Arie, Glow operates from Palo Alto and Tel Aviv. The company describes itself as an endpoint AI business rebuilding protection around the risks created by modern software and autonomous systems.

The endpoint has become an uncontrolled software layer

Traditional endpoint products were designed around a clearer model of work: known employees using approved applications on managed devices.

AI has disrupted that structure.

Employees can now install new tools, connect browser extensions and run autonomous agents with limited security review. Some applications may access sensitive files, credentials or internal systems before security teams even know they exist.

Glow argues that reacting after suspicious activity is no longer enough. Its platform is designed to create a continuous record of the people, devices and software operating across an organization.

AI agents are being used as security operators

Glow uses specialized AI agents to analyze endpoint activity, interpret risk according to company policy and create controls before an incident develops.

Rather than forcing security teams to switch between several point products, the platform aims to provide one operational view across software, devices and users. It can then recommend or execute actions intended to reduce the organization’s attack surface.

The company’s proposition is not simply faster threat detection. It is to control which software can run, what that software can access and whether its behavior fits the organization’s security rules.

That places Glow closer to an endpoint operating layer than a conventional alerting dashboard.

A large round raises the deployment expectations

Glow has entered the market with substantial funding, a unicorn valuation and a team of more than 100 employees, according to its launch announcement. Its LinkedIn profile lists the business as having between 51 and 200 employees.

The capital gives Glow room to invest heavily in engineering, customer deployment and commercial expansion. It also places the company under pressure to prove that its prevention-first model works across complex enterprise environments.

Endpoint controls can easily become disruptive when they block legitimate software or interrupt employee workflows. Glow will need to show that its agents can distinguish meaningful risk from ordinary business activity without creating another layer of approval delays.

Security teams will judge the product on what it prevents

Cybersecurity vendors often compete on how quickly they detect and contain an attack.

Glow is proposing a different performance measure: how much risk can be removed before the attack begins.

That promise will depend on endpoint visibility, accurate policy interpretation and the quality of automated decisions. Enterprises will want evidence that the system reduces incidents without giving autonomous security agents too much control.

The company has secured the capital to compete in one of cybersecurity’s most established categories. Its harder task is proving that endpoint protection can become proactive without becoming unpredictable.

Source : Glow Official Announcement