> ## Documentation Index > Fetch the complete documentation index at: https://documentation.uponai.com/llms.txt > Use this file to discover all available pages before exploring further. # AI QA Metrics > Definitions for every metric and term used in AI QA results. This page explains every metric and term in AI QA so you can interpret your call analysis results. When a metric fails, see [Address Metric Issues](/ai-qa/address-metric-issues) for step-by-step guidance on how to fix it. ## Performance Metrics ### Latency | Metric | Description | | ------------------- | ------------------------------------------------------------------------------------------------------------------ | | **Average Latency** | End-to-end delay between user speaking and agent beginning spoken response. Measured in seconds — lower is better. | | **Latency P50** | 50th percentile (median) latency. Half of all responses are faster, half are slower. | ### Sentiment Analysis | Metric | Description | | --------------------------------- | ------------------------------------------------------------------------------------------------------------ | | **User Sentiment** | Emotional state of the caller inferred from speech content, tone, and pitch — positive, negative, or neutral | | **User Positive Sentiment Rate** | Percentage of user interactions with positive sentiment | | **User Negative Sentiment Rate** | Percentage of user interactions with negative sentiment | | **Negative Sentiment Rate** | Overall rate of negative sentiment in the conversation | | **Agent Sentiment** | Emotional tone expressed by the AI during speech | | **Agent Positive Sentiment Rate** | Percentage of agent responses with positive sentiment | | **Agent Natural Tonality Rate** | How natural and human-like the agent's tone sounds | ### Transcription Metrics | Metric | Description | | --------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- | | **WER (Word Error Rate)** | Percentage of words incorrectly transcribed. Calculated as: `(Substitutions + Insertions + Deletions) / Total Words × 100%`. Lower = better. | | **Mistranscribed Entities** | Count of specific entities (names, dates, numbers) incorrectly transcribed. Only critical factual errors that change meaning are counted. | ### Call Quality Metrics | Metric | Description | | ------------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | | **Interruptions** | Count of times the user interrupted the agent. High counts may indicate the agent speaks too long or doesn't respond appropriately. | | **Avg. Interruptions** | Average interruptions per call across the cohort | | **Agent Naturalness** | How human-like the agent sounded — pronunciation, intonation, pacing, turn-taking, absence of robotic patterns. Higher = more natural. | | **Natural Tonality Rate** | Percentage of agent speech that sounds natural in tone and delivery | ## AI Accuracy Metrics | Metric | Description | | -------------------------- | -------------------------------------------------------------------------------------------------------------- | | **LLM Hallucination Rate** | Rate at which the LLM generated incorrect or fabricated information not supported by context or knowledge base | | **Agent Hallucination** | How often the agent hallucinated. High values mean the agent may be providing incorrect information to users. | | **KB Recall** | How effectively the agent retrieved and used relevant knowledge base information. Higher = better. | ## Tool and Function Metrics | Metric | Description | | ---------------------------- | ------------------------------------------------------------------------------------------------ | | **Tool Call Accuracy** | Rate at which the agent correctly invoked tools. Higher = agent uses right tools at right times. | | **Tool Call Inaccuracy** | Rate at which the agent invoked incorrect tools (inverse of Tool Call Accuracy) | | **Custom Tool Success Rate** | Percentage of custom tool calls that completed successfully | | **Avg Custom Tool Latency** | Average time for custom tools to execute and return results | ## Conversation Flow Metrics | Metric | Description | | ------------------------------ | ----------------------------------------------------------------------------------------- | | **Transition Accuracy** | Accuracy of transitions between conversation nodes. Higher = agent follows intended flow. | | **Node Transition Inaccuracy** | Rate of incorrect node transitions in conversation flows | ## Call Resolution Metrics | Metric | Description | | ------------------------ | ------------------------------------------------------------------------------ | | **Call Resolution Rate** | Percentage of calls successfully resolved per your defined criteria | | **Average Score** | Overall quality score calculated from resolution criteria and weighted scoring | | **Calls Analyzed** | Total calls analyzed in the cohort | ## Transfer Metrics | Metric | Description | | ------------------------- | ------------------------------------------------- | | **Transfer Success Rate** | Percentage of calls successfully transferred | | **Transfer Wait Time** | Average time users wait before transfer completes | ## Statistical Terms | Term | Description | | ----------------------- | -------------------------------------------------------------------------------------------------- | | **P50** | 50th percentile (median) — half above, half below | | **Cohort** | A filtered set of calls sharing common characteristics, analyzed with the same resolution criteria | | **Sampling Percentage** | Percentage of matching calls included for analysis | | **Weekly Max** | Maximum calls analyzed per week regardless of sampling percentage | ## Resolution Criteria Terms | Term | Description | | -------------------------- | ---------------------------------------------------------------------------------- | | **AI Evaluated Condition** | Qualitative criteria evaluated by AI from transcripts (e.g., "Call resolved") | | **Performance Metric** | Quantitative threshold a call must meet (e.g., latency \< 2s) | | **Weighted Scoring** | Assigns different weights to criteria to prioritize certain conditions over others | | **Calibration** | Manual override of automatic metric evaluations for a specific call | Some metrics show "N/A" when there isn't sufficient data or when the metric doesn't apply to a call type (e.g., transfer metrics on non-transfer calls).