Pluto Security Bets $42 Million on Controlling AI Workspaces

Pluto Security is out of stealth. The company announced on October 13, 2026, that it has raised $42 million to secure AI workspace environments and tools, giving the crowded security market another company eager to police the machines making decisions inside businesses.

Pluto has reached more than $2 million in annual recurring revenue and secures more than 1 million endpoints globally. It serves more than 40 enterprise customers, while more than 30 enterprise customers include Oscar Health, Workato, Sixt, and AlphaSense.

The company started selling its product in April 2026, then reached those figures within the same year. Founded in 2025, Pluto has grown to more than 50 employees across the United States and Israel, including 40 employees in the U.S. and Israel.

Two Rounds, One AI Security Bet

Pluto’s funding includes an $8.5 million seed round led by TLV Partners and a $34 million Series A led by Jump Capital. Together, those rounds account for the company’s $42 million in total funding.

The financing also includes investors Ariel Maislos, Yevgeny Dibrov, Nadir Izrael, Slavik Markovich, Asaf Ezra, Sharin Fisher Dibrov, and Idan Tendler. The latest round was approximately $34 million, giving Pluto fresh capital to expand its platform as companies add AI tools faster than security teams can inspect them.

That mismatch sits at the center of Pluto’s pitch. “Security has traditionally been built around stopping things, but that model breaks down when the business is moving faster than security can evaluate every new tool,” said Shahar Bahat, Pluto’s CEO and co-founder.

Bahat co-founded Pluto with Tal Ofer Regev and Gil Maman. The company is built around a shift from securing only users and endpoints to monitoring what AI agents do inside enterprise systems — a change Bahat summarizes plainly: “We’re moving from user behavior to agent behavior.”

Watching Agents Before They Break Something

Pluto’s platform combines endpoint visibility, contextual risk analysis, and real-time enforcement. It provides visibility, risk assessment, and real-time control over AI tools and components, including the ability to restrict access to payment APIs, sensitive data, and trusted MCP servers.

The platform includes Explorer, Risk Radar, Space Shield, and Marketspace. Those functions are designed to help organizations identify AI components, assess their risks, and enforce controls while those components operate inside an AI workspace.

Pluto can intervene while an AI agent is working by stopping an action or prompting for confirmation. That matters because an agent may not need malicious intent to create a security problem; it only needs access, an instruction, and enough freedom to act before anyone checks its work.

The platform can also inject context back into an active session. “We can inject context back to the session, and this way I can change how the agent is working,” Bahat said.

That approach treats security as an active control layer rather than a fence built around a finished system. The distinction is important for AI workspaces, where tools, connectors, skills, add-ons, and agents can interact in ways that are difficult to review from a static list of approved software.

Pluto launched Plutonium in April, a free platform for risk checking AI skills, connectors, and add-ons. Thousands of security professionals use and contribute to Plutonium, giving Pluto a public venue for examining AI components alongside its enterprise product.

Pluto now has funding, customers, revenue, and a platform aimed at one of enterprise security’s messier problems: controlling AI systems while they work, not after the damage report arrives. Whether its model holds up as AI workspaces grow more complex will depend on how well those controls handle real business activity — because adding another dashboard has never been the hard part.

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