Kuldeep Paul

Roll out AI governance with MDM across your whole fleet: push Bifrost Edge through Jamf, Intune, or Kandji so endpoint AI traffic is governed automatically. Surveys of enterprise workforces now put the share of employees using unsanctioned AI tools above 80 percent, according to UpGuard's State of Shadow

AI governance for regulated industries fails at the endpoint, where employees run ungoverned AI tools. Bifrost extends that governance to every machine. Regulated industries operate under audit, data residency, and access control requirements that apply to every system touching sensitive data. AI governance for regulated industries has to extend those

Bifrost is the open-source AI gateway for building a complete AI audit trail and governing every AI interaction, from the data center to every laptop. Most enterprises can account for only a fraction of the AI requests their employees send each day, because the only traffic that gets logged

Bifrost is one control plane for governing AI coding agents like Claude Code, Cursor, and Codex, with Bifrost Edge extending it to every machine. AI coding agents like Claude Code, Cursor, and Codex now run across hundreds or thousands of developer machines in a typical engineering organization, and most of

Bifrost is the open-source AI gateway that governs MCP security risks centrally, while Bifrost Edge extends that same governance to every endpoint machine. The Model Context Protocol (MCP) lets AI applications discover and call external tools at runtime, which means every connected MCP server becomes a new trust boundary

MCP server governance controls which MCP servers, tools, and users are allowed across your AI traffic. Bifrost enforces it at the gateway and the endpoint. Most organizations cannot produce a list of the MCP servers running inside the AI tools their employees use every day. Model Context Protocol (MCP) servers