×
Quality shouldn’t depend on reviewing a small sample of customer interactions. Every conversation contains insights that can improve compliance, coaching, customer experience, and operational performance.
Lumina Datamatics’ AI Automated QC combines AI-powered quality scoring, compliance monitoring, sentiment analysis, resolution quality, and coaching intelligence to evaluate interactions across voice, chat, and email, helping CX teams improve quality at scale.
Manual QA reviews only a small percentage of customer interactions, leaving compliance risks, coaching opportunities, and customer issues hidden across the majority of conversations.
Without continuous quality intelligence, coaching is delayed, recurring issues remain undetected, and quality scores rarely connect to broader business outcomes.
Transform every customer conversation into actionable quality intelligence with AI-powered monitoring across voice, chat, and email.
Bring together voice transcripts, chat conversations, emails, CRM history, ticket context, and QA metadata into a unified quality intelligence layer.
Automatically evaluate resolution quality, empathy, process adherence, compliance, knowledge accuracy, and next-best-action behavior using AI-powered scorecards.
Detect sentiment deterioration, compliance violations, policy risks, escalation signals, and interaction anomalies before they become larger operational issues.
See how AI evaluates customer interactions by configuring the communication channel, interaction type, and risk profile.
The interactive prototype demonstrates quality scores, compliance findings, coaching recommendations, and business-impact insights, helping quality teams identify risks earlier and prioritize coaching opportunities.
The interaction met resolution objectives but showed reduced empathy and a missed compliance disclosure. Similar interaction patterns indicate an increased likelihood of repeat contact.
Prioritize coaching on empathy and mandatory disclosures while reviewing related interactions for recurring compliance gaps.
*The experience above is illustrative. Try the AI Automated QC Prototype to explore the actual interface.
Quality management should do more than assign scores. By connecting every interaction to compliance, coaching effectiveness, customer effort, and business outcomes, AI Automated QC helps organizations identify recurring issues earlier and continuously improve customer experience.
Scores voice, chat, and email interactions instead of relying on manual sampling.
Expands quality visibility and reduces blind spots.
Evaluates compliance, process adherence, empathy, accuracy, resolution quality, and next-best-action behavior.
Creates consistent scoring and accelerates QA cycles.
Identifies frustration, confusion, dissatisfaction, and high-effort customer journeys.
Improves coaching effectiveness and root-cause analysis.
Detects missing disclosures, policy deviations, incorrect claims, and sensitive-language risks.
Strengthens regulatory, brand, and process compliance.
Compares AI and human QA scores while supporting dispute reviews and scorecard calibration.
Improves evaluator consistency and confidence in AI scoring.
Recommends coaching priorities and training focus areas from real interaction patterns.
Moves QA from auditing to continuous performance improvement.
AI Automated QC connects interaction analysis, AI scorecards, compliance monitoring, and coaching intelligence into a continuous improvement workflow.
Capture voice, chat, email, CRM, and ticket context.
Evaluate every interaction using AI-powered quality scorecards.
Identify compliance, sentiment, resolution, and escalation risks.
Recommend targeted coaching based on agent and team performance.
Turn interaction insights into continuous quality and operational improvement.
See how AI-powered quality monitoring can expand quality coverage, strengthen compliance, improve coaching effectiveness, and continuously enhance customer experience.
AI Automated QC expands quality coverage and prioritizes interactions requiring attention, while human quality analysts continue to play an important role in calibration, dispute resolution, and situations requiring contextual judgment.
The solution is designed to support automated quality scoring across voice, chat, and email interactions, depending on transcription quality, available data, and system integrations.
AI evaluates resolution quality, compliance, sentiment, empathy, process adherence, knowledge accuracy, escalation handling, and next-best-action behavior to provide comprehensive quality insights.
AI identifies agent-level and team-level performance patterns, recommends coaching priorities, and highlights real interaction examples that help managers deliver more personalized and effective coaching.
