AI Governance

Set up Bifrost with Patronus AI for hallucination detection and LLM safety evaluation, screening prompts and responses for PII, toxicity, and injection. Large language models generate fluent, confident text that is sometimes factually wrong, and those errors pass through to users without raising any failure in application logs. For teams

Bifrost integrates AWS Bedrock Guardrails as a gateway-layer guardrail profile, enforcing PII redaction and content filtering across every LLM provider without per-application configuration. This walkthrough covers IAM auth, profile setup, CEL rule targeting, and a working two-rule configuration for input and output scanning. AWS Bedrock Guardrails provides

The top LLM governance platforms for 2026, compared on access control, policy enforcement, and compliance. Bifrost is the best choice for enterprises running mission-critical AI workloads that require best-in-class performance, scalability, and reliability. Enterprise AI usage now spans dozens of teams, hundreds of API keys, and multiple

Bifrost Access Profiles bring enterprise AI governance to large teams: reusable policies that auto-provision governed virtual keys with budgets and model limits. Enterprise AI governance fails most often at the access layer: who can call which models, with what budget, and which tools they can reach. IBM's

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