AI Governance

AI governance is the set of policies and controls that keep enterprise AI secure, compliant, and cost-bounded. Learn why it matters and how Bifrost enforces it. AI governance is the set of policies, controls, and processes an organization uses to manage how AI systems are accessed, used, secured, and

Learn how to stop your AI from leaking PII or returning unsafe output to customers by enforcing real-time guardrails at the gateway layer with Bifrost. Customer-facing AI applications fail in two costly ways: they return personally identifiable information (PII) that should never leave the system, and they produce

Bifrost is an open-source AI gateway that brings Claude Code governance to enterprise teams with virtual keys, per-developer budgets, RBAC, and signed audit logs. Claude Code runs in the terminal with full user-level privileges: it reads source files, executes shell commands, connects to MCP servers, and sends

Governing MCP tool execution means controlling which tools a model can run and who can run them. Bifrost enforces approval, filtering, and audit at the gateway. By default, the Model Context Protocol treats tools as model-controlled: a language model can discover and invoke them automatically based on the conversation.

Shadow AI is the unsanctioned use of AI tools inside enterprises. Learn how it emerged, the risks it creates, and how AI governance and security contain it. Shadow AI is the use of AI tools, models, and applications by employees without the knowledge, approval, or oversight of IT and security

Claude Code governance starts at the gateway. Bifrost secures agent access with virtual keys, credential isolation, MCP tool filtering, and immutable audit logs. Claude Code authenticates with a raw provider API key, reads entire repositories, runs shell commands, and calls external MCP tools from a single terminal session. When every