AI Governance

Build per-team cost attribution for AI usage with Bifrost: track LLM spend across teams using hierarchical budgets, virtual keys, and exportable telemetry. When LLM usage arrives as a single provider invoice, platform teams cannot tell which team, application, or project drove the spend, and per-team cost attribution becomes

Learn how to restrict GPT-5 access to a single team with virtual keys in Bifrost, the open-source AI gateway, with model filtering, budgets, and rate limits. GPT-5 is one of the most capable and most expensive models available through the OpenAI API, and uncontrolled access across an

AI governance for production AI teams means controlling access, cost, and compliance across every model. Learn the core controls and how to enforce them at the gateway. AI governance is the set of controls that determine which teams and applications can call which models, under what budgets, rate limits, and

Set up virtual keys for LLM access control with budgets, rate limits, model allowlists, and audit logs. A complete configuration guide using Bifrost. Virtual keys for LLM access control solve the most common governance problem in production AI: how to give every team, project, and customer their own bounded view

A complete guide to AI governance for enterprise LLM deployments, covering access control, cost management, and compliance enforced at the gateway layer. Enterprise teams running large language models in production face a governance gap that no policy document can close. AI governance for enterprise LLM deployments has shifted from voluntary

AI governance in regulated sectors requires per-team controls, full audit trails, and policy enforcement at the gateway layer. Here is how Bifrost delivers them. AI governance in regulated sectors has moved from advisory concern to operational requirement in 2026. Healthcare providers must now disclose AI involvement in patient care