A supervisor sampling a few calls a week is not doing quality assurance. They are doing quality anecdotes.
“Good morning, this is Priya from [MASKED]. May I confirm the last four digits of your account?”
Mandatory disclosure was never read out before verification began.
“I understand this is frustrating, let me see what I can do.” Acknowledged once, then moved on.
A team of thirty agents produces several thousand conversations a month. A supervisor with a spreadsheet gets through perhaps two hundred of them, chosen by whatever was convenient.
Everything downstream inherits that: the trend line, the coaching, the assurance you give the business that things are fine. A missed disclosure in the calls nobody opened is not a smaller problem than one in the calls they did.
Upload a batch or point us at a CSV of recording URLs. Coverage stops being a function of how many hours your supervisor has.
Every parameter returns the transcript lines it was judged on, so a score an agent disputes becomes a sentence you both read rather than an argument about the tool.
Each score carries a confidence figure. The calls the model hedged on are the ones worth your analyst’s time: a far better use of them than re-checking the obvious ones.
Customer and agent sentiment are scored separately, with the turning points timestamped, so you can jump to the moment a call went wrong.
An example of the shape, not a set we ship. Your parameters, your weights, your severities.
First contact resolution needs to know whether the same customer came back about the same issue, and that lives in your helpdesk rather than in a recording. You can score whether the agent resolved it on this call; linking contacts over time is not something we do.