Call Intelligence
The call ends. The evidence starts.
Every completed conversation is recorded, transcribed and analysed within seconds—giving your teams QA, customer facts, outcomes and exceptions without relying on a manual sample.
After every completed callCall intelligence
Processing 01 / 04
Live processRecording closed and attached to the call record.
- Now01HangupRunning
Recording closed and attached to the call record.
- Queued02TranscriptWaiting
Speakers separated and the conversation transcribed.
- Queued03AnalyseWaiting
QA, behaviours, outcomes and customer facts evaluated.
- Queued04Write + alertWaiting
Structured fields written back; exceptions routed.
Example extraction
- intent
- Cancel → save opportunity
- objection
- Price / perceived value
- competitor
- Named competitor plan
- budget_signal
- Sensitive to monthly cost
- sentiment
- Frustrated → regulated
QA dimensions
- Emotional handling
- Diagnosis
- Framework execution
- Influence & resolution
- Care & compliance
- Outcome
Example output shown. Fields, rubrics, retention and downstream actions are configured for each deployment.
Operational analytics
Find the pattern. Then open the calls behind it.
Move from a single transcript to fleet-level evidence. Segment quality by campaign, language, agent version, caller population or outcome; identify where performance is drifting; then inspect the exact calls and decision traces that created the signal.
Illustrative analysis · demo datasetProduction call intelligence
Last 7 daysAll campaignsAll languages
Seven-day trendResolution quality
MTWTFSS
Patterns to investigateOpen the calls behind the signal
- 01Repeat explanation18 callsFalling
- 02Incomplete outcome11 callsReview
- 03Tool path abandoned7 callsStable
Review queuecall_2841 · Verification incomplete
AI verdict: review · confidence 0.72 · transcript and decision trace attached
QA for every call
Measure the behaviour, not just the outcome.
A successful outcome can still hide poor conduct. The rubric evaluates how the result was reached and can hard-flag critical care or compliance misses.
Emotional handling
Did the agent read the caller’s state and de-escalate before solutioning?
Diagnosis
Did the agent reach the real interest or root cause, not just the presenting issue?
Framework execution
Was the right skill used at the right phase — and were blocked levers respected?
Influence & resolution
Was value created or traded, the objection handled, a clear commitment reached?
Care & compliance
Were disclosures made, vulnerability handled, and guardrails honoured?
Outcome
Was the result achieved — and not at the cost of the relationship?
Structured extraction
The call contains customer data your forms never captured.
Decide what matters to your operation, then extract it consistently from the transcript and write it into the right downstream record.
intent
Illustrative value: Cancel → save opportunity
objection
Illustrative value: Price / perceived value
competitor
Illustrative value: Named competitor plan
budget signal
Illustrative value: Sensitive to monthly cost
sentiment
Illustrative value: Frustrated → regulated
commitment
Illustrative value: Stay 6 months · add X · no discount
disposition
Illustrative value: Saved
next action
Illustrative value: Confirmation email · 48h check-in
Human calibration
Let automation find the calls. Let people sharpen the standard.
Low-confidence verdicts, hard policy failures and unusual customer moments can enter a focused review queue. A reviewer confirms or overrides the evaluation, adds an explanation and turns that judgment into a clearer rubric or a new simulation scenario.
Detect
Aggregate evaluations expose drift, repeated failure patterns and exceptions worth attention.
Review
Human reviewers see the transcript, audio, extracted facts, decision trace and AI explanation together.
Calibrate
Confirmed judgments improve the rubric, escalation threshold and expected behaviour.
Prove again
The production miss becomes a regression scenario before the next agent release.
See the output
Bring a call. Choose what you need to know.
We will map the transcript, QA rubric, extracted fields, alerts and downstream system writes.