Call Monitoring

Automated scoring applies custom QA scorecards, rubrics, metrics, and weights to customer interactions. The system reviews conversations, provides metric-level explanations for why an interaction passed or failed specific criteria, and makes recordings and transcripts searchable by date, agent, score, or custom metadata.

Beyond voice calls, the platform evaluates multi-channel interaction data including SMS messages, emails, documents, and chat transcripts. This provides contact centers with unified quality visibility across channels without requiring separate quality tools for each communication method.

Red-flag detection identifies urgent conversation issues that require immediate supervisor attention, such as improper advice, hostile agent behavior, privacy violations, or customer escalation risks. Supervisors receive automated alerts and can trigger workflow updates to external tools like CRMs and ticketing systems.

Call monitoring identifies recurring missed metrics and performance patterns across interactions. Supervisors can assign targeted coaching recommendations, monitor daily agent progress against improvement plans, and provide practice through structured lessons, quizzes, and AI mock caller roleplay scenarios.

Yes. Organizations configure custom rubrics, scoring criteria, metric weights, and instructions to match specific operational guidelines. Configurable rules also enable automatic rubric selection or interaction exemptions so non-applicable conversations are excluded from grading.

The platform connects with existing workflows through supported data ingestion and APIs. Automated webhooks can push QA results, completed call outcomes, score alerts, and performance signals directly into CRMs, ticketing systems, and internal operational dashboards.