Users often refer to these reports as Auto QA reports or Auto Sampling reports.
In Enthu, both terms point to the same reporting area that shows AI-based evaluation results for sampled calls.
This article explains what these reports show and how to read them.
What these reports are
Auto QA / Auto Sampling Reports show:
Calls evaluated by AI using scorecards
Quality performance across teams and agents
Section-level and question-level AI QA scores
They help you understand how AI evaluations are performing, not just how many calls were sampled.
Where to find Auto QA / Auto Sampling Reports
Go to:
Menu Bar → Auto Sampling Reports
You’ll see three tabs:
AI Evaluation Dashboard
AI Evaluation Report
Section Level Report
All three together make up what users commonly call Auto QA reports.
1. AI Evaluation Dashboard (High-level Auto QA view)
This is the summary view users usually mean when they say “Auto QA report”.
What it shows
Total AI Evaluated Calls
Average QA Score
Average Evaluated Calls per Agent
Quality distribution
Calls are grouped into score ranges:
< 70%
70–90%
> 90%
This helps quickly understand overall AI QA performance.
Note: This criteria is customisable in the profile settings then evaluation settings.
2. AI Evaluation Report (Week-on-week Auto QA report)
This view shows Auto QA performance over time.
How it’s structured
Scorecard → Team → Agent
Week-on-week average AI QA scores
When users call this an “Auto sampling report”
They usually want to:
Compare weeks
Check consistency
See which agents or teams improved or dropped
3. Section Level Report (Detailed Auto QA breakdown)
This is the deep-dive Auto QA report.
What it shows
Individual Auto QAed calls
Overall AI QA score per call
Section-wise and question-wise scores
Clickable call links
Users usually come here when they ask:
“Why is the Auto QA score low?”
Important clarification (keep this simple)
Auto QA / Auto Sampling reports show AI evaluation results
They do not show sampling coverage or rule execution
Calls appear here only after Auto QA runs
Auto-sampled Auto QA calls must be manually submitted to be finalized
Common user statements → What they usually mean
When to use these reports
Use Auto QA / Auto Sampling Reports to:
Track AI QA performance
Monitor quality trends
Identify weak sections or questions
Review AI-evaluated calls
For sampling coverage, rule execution, or call counts, refer to Sampling configuration, not these reports.
When to contact support
Contact support if:
Auto QAed calls don’t appear in these reports
Scores don’t update after submission
Call links are missing or broken