Quality & Insights AI Agent
A supervisor who listens to a few calls a week knows about those calls. Quality listens to all of them and scores each one against your own scorecard, on as many criteria as you need, so your supervisors coach from the whole picture instead of a sample.
What goes wrong
Sampling made sense when every review took a supervisor's afternoon. It still leaves most of your calls unheard, and the habits worth coaching are in the ones nobody heard.
A few calls per person each month can't tell a bad day from a habit, so feedback lands on whoever happened to be picked.
By the time a reviewed call reaches the person who took it, days have passed and they can't remember it, so the feedback doesn't stick.
Scored by hand, a scorecard stays short, because every criterion costs a supervisor time. Scored with AI, review time stops being the limit, so the scorecard can cover what you never had time to check.
A skipped identity check or a missing recording notice turns up when a customer complains, months after the call.
What the platform does
Quality scores each call against your scorecard soon after it ends, and turns the scores into coaching for each person and a clear view of what your customers need.
Recordings come straight from your contact-centre platform, or by upload, and every call is scored, or a share you set. Judgement calls get scored too: whether the tone held, whether the problem was solved. Each mark points to the moment in the call that earned it.
The scorecard is yours, and we help turn it into criteria the model applies the same way on every call. Some are yes-or-no checks, like reading the recording notice. Others are judgements on a scale, like whether the request was understood the first time. Add a criterion and it applies from the next call on.
Scores add up by person and by criterion, across every call they took. A supervisor sees who struggles with what, backed by hundreds of calls instead of three, and opens the calls behind any number. The results also flow into the reporting tools you already use.
The same pass records why each customer called and what got in the way of an answer. You see the reasons rising this week and the ones that rarely resolve on the first call, which is where processes need fixing.
Our clients
Beyond the scores
Thousands of audited calls show how your contact centre really works: what customers ask and what your best people answer. Visor turns that into work you can act on. You don't need AI agents to use Quality, and if you build them, they start from all of it.
The answers your best advisors give, call after call, become knowledge base articles, written from real calls instead of from scratch.
When you build AI agents with Visor, they learn from thousands of audited calls: the questions your customers ask and the answers that resolved them.
The audits show where a script needs a guardrail and which people need training on which criterion, with the calls to prove it.
Reasons that keep coming back without a first-call answer point to the process to change, with the volume behind each one.
