Runlayer has raised $11m to expand its platform as demand for safe AI integration intensifies across industry.
The company has secured $11m in a seed round led by Keith Rabois at Khosla Ventures, with participation from Felicis. Additional supporters advising the firm include David Soria Parra, the Co-Creator of MCP at Anthropic, and Travis McPeak, the Head of Security at Cursor. AI-native companies such as Gusto and Opendoor are already using Runlayer’s technology in production.
Runlayer specialises in helping organisations manage the growing security risks associated with MCP, a rapidly adopted standard that enables AI systems to connect directly to tools, systems and production data. With more than 18,000 MCP servers now active, the company highlights that around 10% are malicious, while many more are easily exploitable. The firm argues that enterprise teams currently lack sufficient visibility and control over how AI tools interact with sensitive systems, leaving businesses with a stark choice between blocking MCP entirely or accepting significant operational risk.
The new capital will support Runlayer’s plans to scale enterprise-grade MCP security infrastructure. This includes expanding threat detection capabilities, enhancing fine-grained permission controls integrated with identity providers, improving observability across AI-driven actions, and developing a curated MCP catalogue to ensure developers only access vetted, trustworthy tools. The company intends to make the platform deployable either within a customer’s virtual private cloud or via its own cloud environment, strengthening operational flexibility.
Runlayer believes MCP will become the defining interface for AI over the next two decades, similar to the role APIs played in the evolution of modern software. Its platform aims to enable businesses to adopt AI agents in production securely, combining strong protection mechanisms with the ability to innovate at scale. The company positions its technology as essential for organisations seeking meaningful AI transformation without introducing operational chaos.
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