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Back to Generative AI Features Quality AI uses LLM-powered features to analyze agent-customer conversations. It evaluates agent performance, detects sentiment, identifies compliance gaps, and extracts actionable insights in real time and after the interaction.

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Model Feature Matrix

This table lists Quality AI features and their supported model providers and models. (✅ Supported | ❌ Not supported)

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Features

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Advanced Topic Discovery based on Custom Taxonomy and Resolution Detection

Extracts topics and intents from agent conversations and detects resolution. Surfaces trends and anomalies based on customer sentiment, handle time, and resolution outcomes. Learn more

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Agent Empathy Identification

Identifies instances of agent empathy in conversations where customers expressed negative sentiment. Learn more.

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By Value Adherence Validation

Validates data adherence by comparing extracted metric values against reference data using multilingual LLM analysis. Returns binary adherence scores per metric. Learn more.

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By Value Metric Extraction

Extracts by-value metrics from user, AI Agent, and human agent messages. Learn more.

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By Hold Adherence

Detects when an agent places a user on hold and resumes the conversation. Learn more.

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By Transfer Adherence

Identifies whether the agent informs the customer about a transfer. Learn more.

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Churn & Escalation Identification

Identifies customer churn risk and escalation intents across agent conversations. Learn more.

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Conversation Phase Identification

Identifies conversation phases for phase-level sentiment trajectory and resolution-aware sentiment analysis. Learn more.

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Crutch Word Usage Detection

Detects agent crutch word usage in customer conversations. Learn more.

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Default Script Adherence

Determines agent adherence to default script steps: greeting, branding, privacy policy, customer verification, hold etiquette, and call closing. Learn more.

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GenAI-based Agent Answer Adherence and Customer Trigger Detection

Verifies agent adherence and detects customer triggers without requiring utterance configuration or training. Learn more.

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Generating Similar QM Utterance Suggestions

Generates semantically similar phrases during design time. Learn more.

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Post Conversation Sentiment Analysis

Generates post-interaction sentiment and emotion moment insights for agent conversations. Learn more.

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Sentiment Analysis

Displays a real-time sentiment indicator during active chat conversations, updating dynamically as the conversation progresses. Learn more.

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Topic Modelling

Extracts popular topics and intents from agent conversations. Learn more.