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a telecom subscription call center

AI Call Quality Auditing

  • 8,000+ calls/day
  • 85% fewer wrong-booking complaints
  • Fully automated

The problem

A call center runs thousands of agent-customer calls a day. No human team can listen to all of them, so compliance issues and wrong bookings slip through unnoticed.

What I built

  1. Pulls call recordings from an SFTP server.
  2. Transcribes each call (Urdu, noise-tolerant).
  3. Runs an LLM audit scoring every call on 4 compliance parameters: customer consent, two-way communication, pricing clarity, and policy clarity (each yes / no / unclear).
  4. Saves structured results to a database.
  5. A production monitoring dashboard: KPI cards, per-parameter compliance %, trend charts, and a filterable call table with green-tick / red-cross verdicts and drill-down per call.

How it works

  • SFTP ingestionparallel workers, resumable and incremental.
  • WhisperUrdu speech-to-text for transcription.
  • OpenAIthe 4-parameter compliance analysis on every call.
  • Python + SQLitepipeline and structured results.
  • FastAPI + Chart.jsthe monitoring dashboard.

The result

  • 8,000+ calls audited every day, automatically.
  • Cut wrong-booking complaints by ~85%.
  • A live dashboard so the team sees compliance at a glance and drills into any call.

See it run

Dashboard demo. All data is masked — mobile numbers hidden, no real transcripts shown.

Have calls or data you can't manually review? Let's talk.

Tell me where your team is losing time. If I can automate it, I'll show you how.