Stop Shipping Ungoverned AI: Add Policy Gates, Audit Trails, and Compliance to Every LLM Call

Your AI Solution Works. But Can You Prove What It Did? You shipped the chatbot. The coding assistant is saving your team hours. The RAG workflow is answering questions from internal docs. Product is happy because the demo works. Then the harder questions show up: Can you show which policy checks ran before a model call? Can you prove what happened for a specific runId last week? Can you redact sensitive input before it reaches the provider? Can you generate evidence for audits instead of screenshotting dashboards? That is where most AI solutions fall apart. A successful model response is not the same thing as governed AI. The Real Problem in Production AI Most teams still ship LLM features with a thin wrapper around the provider SDK: Accept a prompt. Send it to OpenAI, Anthropic, Gemini, or Bedrock. Return the response. Hope logs are enough later. That works until you need to answer operational or compliance questions: What exactly was sent to the model? Was sensitive data redacted fir