Best AI governance platforms for LLM applications (2026): Eval, audit, and enforce

AI governance for LLM applications encompasses evaluating model outputs, recording production behavior, controlling access, and enforcing policies across development and production phases. Effective governance requires eval-time scoring, production audit, access control, and runtime enforcement to ensure compliance and mitigate risks. Braintrust emerges as a leading AI governance platform, offering a unified workflow that integrates evaluation, production tracing, offline evaluation, CI release gating, and human review, all while maintaining audit-grade tracing, role-based access control (RBAC), and compliance certifications such as SOC 2 Type II and HIPAA. While Braintrust excels in evaluation and audit capabilities, other platforms like Galileo focus on low-latency runtime protection, Credo AI on portfolio-level governance, Fiddler AI on classical ML monitoring combined with LLM oversight, and Patronus AI on regulated-domain evaluator coverage. Braintrust's deployment flexibility, including hybrid and self-hosted options, ensures data residency and security, making it suitable for regulated industries seeking comprehensive governance solutions for LLM applications.