Pluto Security raises $42M as AI gives enterprise security teams a new headache
Pluto Security has emerged from stealth with $42 million to help businesses manage security risks created by fast-growing use of AI tools. The company argues that conventional security software may not give organisations enough visibility into how employees and AI agents use these tools, or what they build with them.
CEO Shahar Bahat says newly released AI tools can appear in company systems within two hours, and around 60% of the risks Pluto detects involve apps built by non-developers, particularly in finance. One example was a finance employee’s customer-management app at a Fortune 500 company that was exposed to the internet. Pluto says it began selling in April, has passed $2 million in annual recurring revenue and serves more than 30 enterprise customers, including Oscar Health, Workato, Sixt and AlphaSense; its funding includes an $8.5 million seed round and a $34 million Series A.
- Pluto Security raised $42 million to address enterprise AI security risks.
- About 60% of risks it detects involve tools built by non-developers.
- The startup says it has over 30 enterprise customers.
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Businesses use security software to protect their systems and data, but staff also bring in new online tools and build their own apps. Generative AI can help people create software without specialist programming skills, while AI agents can carry out tasks using company systems.
This can make it harder for organisations to see what tools are in use, what information they can access and whether they are secure. Poorly protected apps or services may expose company or customer data, so businesses need ways to track and assess these risks as AI use grows.
Both sides, in good faith
The strongest fair case each way — we don't pick a winner.
The case for
Rapid adoption of AI tools can create security gaps faster than conventional systems can identify them, especially when employees build apps without specialist oversight. Tools that give organisations visibility into AI use and help find exposed data or applications could reduce risks to customers and businesses as well as help security teams keep pace.
The case against
The reported risks may be real, but they do not by themselves establish that a new security platform is the best response; organisations could instead strengthen existing controls, staff training and approval processes. More monitoring software can add cost and complexity, and its value depends on reliably identifying meaningful threats without generating noise or impeding useful experimentation.