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Use AI tools without fear of data leakage
Unbound positions itself as an AI coding agent security broker (AASB) that helps discover, assess, and govern AI coding agents across an organization. It aims to provide visibility, policy enforcement, and governance for AI agents and their connections, focusing on preventing data leakage and unauthorized actions.
Unbound scans an engineering organization to identify AI coding agents, MCP servers, and tool integrations. It inventories agents, their permissions, and configurations, then provides risk scores, policy enforcement, and audit capabilities. The platform includes a policy engine to allow/deny actions, monitor autonomy levels, track drift, and alert on risky MCP connections, with a dashboard showing involved tools, users, and risk factors, plus a risk assessment surface and governance workflows for high-risk operations.
Who it’s for: Engineering and security teams within organizations deploying AI coding agents and MCP integrations
Explicit mentions of free risk assessment, start/free pricing, and book a demo; references to case studies and traction with security teams imply early traction and customer validation
Building data security for Gen AI. Prev: Palo Alto Networks, Adobe | MIT Alum
Cofounder at UnboundSecurity. Building cyber security for gen AI apps. Previously engineering at Shogun, Tophatter, and Adobe Systems.
We help enterprises prevent data loss on consumer Gen AI apps
Unbound Security offers an AI data-loss prevention platform for enterprises, auditing employee use of Gen AI apps, enforcing granular access policies, and blocking leakage of sensitive information from allowed apps. It provides AI app discovery, policy-based guidance to steer usage, and real-time data leakage protection for compliance and privacy.
How Unbound’s homepage introduced itself over the years — each line is the page title the web actually saw, linked to that moment’s archived capture.
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