
EmberQA Voice Analytics for Contact Center QA
- Scores every call with AI rubrics
- Automated transcripts & rubric scoring
- Detects privacy & compliance risks
Intelligent Document Processing for QA and Extraction streamlines quality assurance workflows by analyzing documents, emails, and scored transcripts. Using configured extraction templates, teams capture structured information from interactions to detect red flags, assess compliance risks, and convert customer data into actionable operational insights across contact centers.








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It is an automated solution that applies AI and configured extraction templates to customer interactions, scored call transcripts, and documents. The platform captures structured information, evaluates compliance against custom rubrics, and identifies operational patterns to support quality assurance, operations, and training teams without manual sampling.
Talk to our experts for custom solutions and tailored guidance.

Review written and voice interactions, evaluate agent performance, and extract structured operational insights.

Automate quality assurance scoring across calls and messages to validate records against quality rubrics.
Talk to our experts for custom solutions and tailored guidance.
Evaluate customer interactions across calls, SMS, emails, and documents using customizable quality rubrics rather than manual sampling.
Capture structured data directly from analyzed interactions and scored transcripts to verify records and drive workflows.
Surface urgent quality issues including privacy violations, improper advice, and escalation risks across evaluated interactions.
Connect with our team for guidance on configuring extraction templates, mapping scorecards, and integrating interaction channels.
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