Contact centres and BPO
Contact centre AI audit — every call scored, not a 2% sample
Traditional QA listens to a handful of calls a month and reports on the ones it happened to hear. We transcribe and score the entire month, then reconcile the scores against your telephony data so the pattern arrives with a number attached.
What you are probably seeing
The symptoms that bring people here.
- QA scores look healthy while CSAT and repeat contact do not agree with them.
- Nobody can say which agents drift on regulated language, only which ones were sampled.
- Abandon rate spikes at the same hours every week and the schedule never moves.
- The same ten root causes generate a thousand contacts a month and go unnamed.
Method
How the audit actually runs.
Full-population transcription
Every recording you hand over is transcribed and diarised — not a sample. Coverage is the point: a 2% sample cannot find a behaviour that appears in 6% of calls.
Per-call rubric scoring
Each call is scored against a published rubric covering opening, discovery, objection handling, compliance phrasing, hold and transfer discipline, empathy and close attempt — with the transcript line that produced the score attached.
Reconciliation against telephony data
Scores are joined to handle time, hold time, wrap, transfers, abandon and repeat-contact records so a coaching finding can be costed in minutes and contacts, not adjectives.
Triangulation and self-critique
Every finding is re-tested against a second pass of the evidence. Anything the second pass cannot support is downgraded or dropped before it reaches your board pack.
Deliverables
What lands on the table.
- Ranked findings with severity, an impact estimate and a named owner
- Clickable evidence trail from each finding to the exact call and timestamp
- Agent-level and team-level scorecards against the rubric
- Compliance-language exception list for regulated calls
- A 30/60/90 action plan and a board-ready written report