Call-centre quality monitoring
100% of conversations scored against objective criteria; sampling ends.
Call-centre quality monitoring is an Aginies solution package for the Enterprise Functions sector in the “customer interaction & experience” area. What the agents do: All calls are transcribed; sensitive data is masked; each call is scored against the company’s quality form, with rationale and timestamps. Expected outcomes: 100% evaluation instead of sampling; consistent, objective quality measurement; performance trends and improvement areas visible immediately. The package uses the Speech-to-text, Agent decision traceability, Dashboard analytics layer, Latency tracking capabilities of the Aginies platform and can be watched live through the Call centre quality monitoring, Review response and quality escalation, Bill dispute resolution scenarios in the agent library.
Quality teams can listen to 2% of calls. Scoring is subjective, coaching is late, compliance breaches surface weeks later.
- 01All calls are transcribed; sensitive data is masked.
- 02Each call is scored against the company’s quality form, with rationale and timestamps.
- 03Compliance breaches, repeat complaints and process bottlenecks are flagged automatically.
- 04Agent and team dashboards with trends and coaching suggestions.
- Transcription of every call and automatic scoring against the quality form
- Compliance breach, impolite language and mandatory-phrase checks
- Per-representative coaching note and trend dashboard
- Full coverage instead of sampling; the quality team focuses on exceptions
- Access to call recordings and metadata (switch or recording system)
- The existing quality form and scoring rules
- CRM or switch data that maps representatives to calls
Derived from the linked scenarios: the supervisors, specialist agents, models and systems that run this package.
Summed from the simulation definitions of the linked scenarios; recalculated for your scale in the discovery session.
- 100% evaluation instead of sampling
- Consistent, objective quality measurement
- Performance trends and improvement areas visible immediately
| Calls evaluated | From a 3–5% sample to 100% coverage |
| Quality evaluation effort | 80% lower |
| Time to detect a compliance breach | From weeks to same day |
Target ranges from comparable deployments; baseline and target are fixed together in the first week of the pilot.
Scenario-level approval rules plus the package’s general controls.
- Call centre quality monitoringScore < 60 or compliance breach → team leader review
- Review response and quality escalation1-star review replies and defect escalations → community manager approval
- Bill dispute resolutionGoodwill credit > 75 → team lead approval
- packageA quality specialist validates a sample before scores reach representatives
- packageRecordings processed in Türkiye; personal data masked in transcripts
- 1 · Discovery and design · 2–3 weeksThe 20 most frequent intents and transactions are chosen, identity and approval thresholds written with information security, channel and system integrations listed.
- 2 · Pilot · 4–6 weeksOne channel, a limited customer group; the test corpus runs, a human representative shadows, thresholds tuned on real traffic.
- 3 · Scale-outRemaining channels and transactions added; dashboards, SIEM forwarding and kill-switch handed over; monthly model and rule review begins.
This package’s scenarios in the agent library
Call centre quality monitoring
Every call scored against the rubric, not a sample; compliance breaches and coaching flags ready by morning.
Review response and quality escalation
Reviews classified and answered in brand tone; recurring defects joined with return data and escalated to QA.
Bill dispute resolution
Invoice lines and usage explained in seconds; goodwill credit applied by policy, larger amounts need a lead.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis