The contact center QA agent evaluates customer calls, chats, tickets, and emails to identify compliance risks, knowledge gaps, misrouting, behavioral issues, and resolution quality. It auto-scores interactions using an AI-built QA scorecard, detects repeat-contact risk, and generates agent-level coaching. QA leaders and training teams receive objective, scalable evaluation that reduces manual auditing and improves service consistency across every touchpoint.
The contact center QA agent is an AI workflow that evaluates all customer interactions to assess compliance, soft skills, accuracy, resolution quality, and behavioral patterns for each agent.
The contact center QA agent unifies call transcripts, chats, WhatsApp messages, SMS threads, emails, tickets, chatbot escalations, and survey comments. It cleans, normalizes, tags, translates, and merges conversations into one searchable dataset.
The contact center QA agent applies an AI-generated QA scorecard across compliance, empathy, accuracy, process adherence, ownership, professionalism, and resolution effectiveness, providing unbiased, scalable scoring.
Yes. The contact center QA agent identifies missed resolutions, misinformation, failed troubleshooting, unnecessary escalations, and incorrect expectations that drive repeat contact and suppress first-contact resolution.
The contact center QA agent detects patterns related to weak product knowledge, process misunderstandings, misinformation, and troubleshooting gaps, helping training teams target precise coaching areas.
Yes. The contact center QA agent surfaces compliance risks, routing failures, process gaps, inaccurate knowledge base content, handoff friction, and product issues that impact customer outcomes and churn risk.
The contact center QA agent generates agent coaching digests, team leader insights, QA director trend reports, and CX and operations digests containing evidence, call excerpts, performance clusters, and prioritized coaching steps.