General Analysis provides a comprehensive suite of AI safety tools, including run-time guardrails, red-teaming frameworks, interpretability techniques, observability, and more. As AI systems become increasingly capable, their deployment in high-stakes environments poses significant risks—financial, ethical, and otherwise—where errors can lead to substantial consequences. To address these challenges, we offer access to novel tools and methodologies designed to systematically find model failure modes and enhance model robustness.