### Answer I don't have information about a specific video explaining all the AI Quality Assurance parameters in the available sources. However, you can find comprehensive written documentation covering all the QA metrics and parameters: Terminologies Page – This provides a complete glossary of all metrics used in AI QA, including: [(1) ]() - Latency metrics (Average Latency, Latency P50) - Sentiment Analysis (User/Agent Positive/Negative Sentiment Rates) - Transcription Metrics (WER, Mistranscribed Entities) - Call Quality Metrics (Interruptions, Agent Naturalness) - AI Accuracy Metrics (LLM Hallucination Rate) - Knowledge Base Metrics (KB Recall) - Tool and Function Metrics (Tool Call Accuracy, Custom Tool Success Rate) - Conversation Flow Metrics (Transition Accuracy) - Call Resolution Metrics View QA Results Page – This explains how to interpret the QA dashboard, including the Call QA Overview tab, Detailed Calls tab, and individual Call-Level QA Sheets. [(2) ]() Check out these potentially useful sources: - [Terminologies]() - [View QA Results]() Would you like me to explain any specific QA parameter in more detail?

​ To learn more, see the sources I considered: [[1] Terminologies](https://docs.retellai.com/ai-qa/terminologies) [[2] View QA Results](https://docs.retellai.com/ai-qa/view-qa-results) ​

Feel free to tag @AI Evy with additional questions. I also appreciate feedback, it helps me improve.