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.
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 for step-by-step guidance on how to fix it.
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. |
| 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).
