Voice intelligence software for QA teams
Every conversation reviewed, not a two-percent sample.
askelie's Voice intelligence software transcribes the call and works out who said what. It reads sentiment and topic as it goes, then scores the whole thing against the rubric your QA team already uses.
- Speaker personas
- Rubric grading
- Topic & sentiment analytics
What it does
Speech in, evidence out.
Here's what our voice intelligence software actually does, end to end.
Transcribes with the audio attached
Every line in the transcript is time-stamped, so clicking any line jumps straight to that moment in the recording.
Knows who was speaking
Once you've told it who's on the call, it correctly attributes each part of the conversation to the right speaker, so coaching notes and quality scores land on the right person.
Scores against your rubric
Your existing scorecard, with its own weightings, applied to every conversation, not to whichever handful someone found time to review.
Use cases
Where teams point it first.
- 01
QA reviews a small sample of calls and coaching is argued from anecdotes.
Every conversation is scored on the same rubric, so a trend is something you can point at instead of something you sense.
- 02
A complaint arrives about a call that happened three weeks ago.
The transcript, the speaker attribution and the audio are together in one place, with an audit trail of any edit.
- 03
Nobody can say which topics are actually driving contact volume.
Topics and sentiment are read as the conversation is processed, so volume and mood become a chart rather than a guess.
- 04
Quality data lives in a spreadsheet that someone maintains by hand.
Scores and analysis export on a schedule to the system that already runs your reporting.
How to use it
Four steps from first recording to a trend line.
- /elie-voice/new
Create a voice app
One app per conversation type: collections calls behave nothing like new-business calls, and they shouldn't share a rubric.
- /personas · /grading
Describe the speakers and the scorecard
Name who you expect on each side of the call, then paste in the rubric your QA team already argues about. Weight the criteria that matter.
- /conversations
Feed it conversations
Upload recordings or connect your telephony store through IntELIEKonnect. The pipeline reports progress per conversation, and failures stay visible.
- /topics-sentiment · /analytics · /export
Read the trend, then send it on
Score distribution by team, topic volume over time, sentiment against outcome. Export the whole thing when someone asks for it in a spreadsheet.
Works well with
Back to the platformaskKIRA
Ask questions across your conversations and get answers backed by real citations, the same way you can with your documents.
ExploreintELIEdocs
The paperwork a conversation refers to, processed by the same pipeline.
ExploreIntELIEKonnect
Collects recordings from where they are stored and delivers scores back out.
ExploreSend us one recorded call and your scorecard.
We'll run it through our voice intelligence software: transcribe it, attribute the speakers and grade it against your own rubric, then show you what the same thing looks like across a month.