AI Governance

Governing Enterprise AI and Data: The Leading Platforms

Governing Enterprise AI and Data: The Leading Platforms

TL;DR * Enterprise AI governance platforms control which teams reach which models, cap spend per consumer, filter sensitive data in prompts and responses, and record audit evidence for compliance reviews. * AWS, Azure, and Google Cloud now offer token quotas, guardrails, and MCP tool governance, but each assembles them from several

Policy-Based Governance at the Gateway: One Control Plane for Every AI Call

Policy-Based Governance at the Gateway: One Control Plane for Every AI Call

TL;DR * Gateway-enforced AI policy turns written rules for access, spend, routing, and content safety into checks that run on every model and tool request. * A Cloud Security Alliance survey published in April 2026 found that 82% of organizations had discovered previously unknown AI agents in their environments in

AI Guardrails at the Gateway: Catching Hallucinations on Every Model Response

AI Guardrails at the Gateway: Catching Hallucinations on Every Model Response

TL;DR * AI guardrails at the gateway validate every model response before it is returned, so one policy covers every application and provider. * Bifrost guardrail rules use CEL expressions on request metadata (model, provider, headers, team, virtual key) and an apply_to of input, output, or both; linked profiles inspect

AI Agent Guardrails: Policies and Controls for Autonomous Agents

AI Agent Guardrails: Policies and Controls for Autonomous Agents

TL;DR * AI agent guardrails are runtime policies that a gateway checks before every model call and every tool execution, blocking, redacting, or transforming traffic that violates the rule. * The gateway is the correct enforcement point because it sees every request an agent makes, cannot be bypassed by the agent

AI Agent Governance: Identity, Permissions, Budgets, and Lifecycle in Production

AI Agent Governance: Identity, Permissions, Budgets, and Lifecycle in Production

TL;DR * AI agent governance is the operational practice of treating every production agent as a distinct identity with its own permissions, budget, audit trail, and lifecycle events, rather than as an anonymous consumer of a shared human API key. * Bifrost implements agent identity with virtual keys, which carry per-

AI Governance Strategy for Platform Engineering Teams

AI Governance Strategy for Platform Engineering Teams

A guide to designing an AI governance strategy that fits an internal developer platform, from virtual keys and budgets to MCP tool governance.

How to Govern AI Coding Agents at Scale

How to Govern AI Coding Agents at Scale

TL;DR * Gartner predicts 90% of enterprise software engineers will use AI code assistants by 2028, up from less than 14% in early 2024, and much of that traffic can leave developer laptops outside any policy layer. * Governing AI coding agents at scale takes two layers: an AI gateway that